Dissertations / Theses: 'FORECASTING TOOL'

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Ljungström, Erica. "ISAT : Interactive Scenario Analysis Tool for financial forecasting." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-177128.

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Målet för denna studie har varit att skapa en första version för ett verktyg i vilket analytiker inom finans kan skapa sina långsiktiga scenarion och väga olika rikser samt möjligheter mot varandra.Idén till ett sådant verktyg har funnits inom företaget i flera år, men de tidigare idéerna har varit för specifika för att kunna användas. Detta har främst berott på tidsbrist samt att de som utvecklat dem inte har haft tillgång till en bra utvecklingsmiljö.De enda begränsningarna för verktyget har varit 1) ”Det behöer kunna visa inverkan av manipuleringar”, 2) ”det behöer finnas såmycket funktionalitet som möjligt, utan att det finns knappar överallt” och 3) ”det få inte ädra nåot av input datan”.Eftersom dessa är abstrakta specificationer behövdes mock-ups, observationer och användbarhetstest för att kunna skapa ett verktyg som förenklar de mest använda manipulationerna. Verktyget måste också låta användaren enkelt ticka i och ur sina manipulationer så att dessa inte behöver göras om varje gång användaren vill testa ett nytt utfall.Observationerna och testerna har visat att användarna jobbar på olika sätt, och därför behövde verktyget vara flexibelt. Detta innebar också att det behövdes både generella samt specifika manipulationer. De visade också att verktyget behövde delas in i två delar, en för att skapa rapporter och en för att visa rapporten. Detta då rapporteringsprocessen ej får ändras.Fokus för denna studie har varit MDI, Människa-datorinteraktion. Detta innebär att den färdiga produkten bör vara intuitiv och väldigt enkel att lära sig att använda för användarna. Detta kan vara svårt då användarna arbetar på mycket olika sätt.Den färdiga produkten för denna studie har lyckats klara alla de mål som satts upp. En mock-up som gjorde användarna nyfikna på programmet, skapades i Java. Det bestämdes därmed att detta var det programmeringsspråk som skulle användas. Ett användargränssnitt som var enkel, men samtidigt hade en komplex funktionalitet lades till.Detta gjorde att användarna frågade sig själva ”Kan det verkligen vara såhä enkelt?” samt ”Varfö har vi inte gjort detta innan?”. Tillslut skapades en fungerande produkt som var både enkel att använda samt att den gjorde många av de enkla beräkningarna åt analytikern.Den enda del som ej blivit fullt implementerad innan slutet för denna studie är mallen för de Excel rapporter som ska skapas av verktyget. Denna del av verktyget utformades av en ekonom som vet vilka grafer som kan vara intressanta att ta med i en rapport. Nu, när verktyget genererar en rapport, genereras endast de grafer som syns i verktyget, totalen för scenariona (uppdelade i olika kategorier) samt alla de manipuleringsrader som skapats för de tre olika scenariona.
The goal with this study has been to create a first version for a tool in which financial analysts can create their long-term scenarios and weigh different risks and opportunities against each other.The idea to such a tool has been around for years within the company, but the earlier ideas were too specific to be usable. This has mainly been due to the lack of time and available tools to realize the ideas.The only restrictions for the tool have been 1) “It needs to show the impact of manipulations”, 2) “it needs as much functionality as possible without having buttons all over it” and 3) “it should not alter any of the input data”.Because these are quite abstract specifications, mock-ups, observations and usability tests have been used to create a tool that simplifies the most used manipulations and enables the user to tick in and out their manipulations so that the manipulation does not have to be redone every time the user wants to test a new outcome.The observations and tests have shown that the users work very differently from each other, and so, the tool needed to be very flexible. This meant that there needed to be both general and specific manipulations which are based on general formulas. It also showed that the tool needed to be split into two parts, one for creating and one for showing reports, because the reporting process should not be altered.The focus of this study has been HCI, Human Computer Interaction. This means that the finished product should be intuitive and also easy to learn how to operate by the users which could be difficult when the users do work in different ways. The resulting product of this study has reached all of the goals. A mock-up that got the users interested in the program was produced in Java, which decided the programming language. A GUI that was simple, yet had complex functionality was added. It made users ask themselves “Could it really be this easy?” and “Why have we not done this before?”. And, at last, a working product were produced, that was both simple to operate and at the same time did a lot of the calculations for the analyst.The only part of the product that has not been fully implemented before the endof this study is the template in which the Excel Report is supposed to be generated. This part of the tool was taken care of by an economist that knew which graphs that could be interesting to create a report of. Now, the tool generates a report with only the graphs that are shown in the tool, the totals for the scenarios (split into different categories) and all of the adjustment rows for the three scenarios.

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Seemann, Thomas. "Prediction markets as forecasting tool in decision processes." Berlin Pro Business, 2008. http://d-nb.info/993592570/04.

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Li, Jin. "FGP : a genetic programming based tool for financial forecasting." Thesis, University of Essex, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343550.

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Yaufman, Mariah B. "A Discontinuous Galerkin-based Forecasting Tool for the Ohio River." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1469035735.

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Choi, Ji Won. "Forecasting potential project risks through leading indicators to project outcome." Thesis, Texas A&M University, 2003. http://hdl.handle.net/1969.1/5973.

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During project execution, the status of the project is periodically evaluated, using traditional methods or standard practices. However, these traditional methods or standard practices may not adequately identify certain issues, such as lack of sufficient identification of warning signs that predict potential project failure. Current methods may lack the ability to provide real time indications of emerging problems that impact project outcomes in a timely manner. To address this problem, the Construction Industry Institute (CII) formed a research team to develop a new tool that can forecast the potential risk of not meeting specific project outcomes based on assessing leading indicators. Thus, the leading indicators were identified and then the new tool was developed and validated. A screening process was conducted through industry surveys after identifying potential leading indicators. Each time, industry professionals were asked to evaluate the negative impact of leading indicators on project outcomes that were identified to measure the impact of leading indicators on project health. Through this process, forty-three leading indicators were acquired finally. Using descriptive statistics, the amount of negative impact of each leading indicator on project outcomes was identified after the analysis of the survey results. Based on these impacts, the tool development was initiated. The tool concept is that no indication of problems based on assessing leading indicators results in the tool output score high. To comply with this concept, specific weights were assigned to each leading indicator to reflect the impact on each project outcome. By this procedure, the Project Health Indicator (PHI) tool was developed. The validation process of the PHI tool was conducted using completed projects and finally negative correlation was observed between project outcomes and health scores generated by the PHI tool.

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BRITO, VICTOR BARBOZA. "FUZZYFUTURE: TIME SERIES FORECASTING TOOL BASED ON FUZZY-GENETIC HYBRID SYSTEM." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2011. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=18536@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
A previsão de séries temporais está presente em diversas áreas como os setores elétrico, financeiro, a economia e o industrial. Em todas essas áreas, as previsões são fundamentais para a tomada de decisões no curto, médio e longo prazo. Certamente, as técnicas estatísticas são as mais utilizadas em problemas de previsão de séries, principalmente por apresentarem um maior grau de interpretabilidade, garantido pelos modelos matemáticos gerados. No entanto, técnicas de inteligência computacional têm sido cada vez mais aplicadas em previsão de séries temporais no meio acadêmico, com destaque para as Redes Neurais Artificiais (RNA) e os Sistemas de Inferência Fuzzy (FIS). Muitos são os casos de sucesso de aplicação de RNAs, porém os sistemas desenvolvidos são do tipo caixa preta, inviabilizando uma melhor compreensão do modelo final de previsão. Já os FIS são interpretáveis, entretanto sua aplicação é comprometida pela dependência de criação de regras por especialistas e pela dificuldade em ajustar os diversos parâmetros como o número e formato de conjuntos e o tamanho da janela. Além disso, a falta de pessoas com o conhecimento necessário para o desenvolvimento e utilização de modelos baseados nessas técnicas também contribui para que estejam pouco presentes na rotina de planejamento e tomada de decisão na maioria das organizações. Este trabalho tem como objetivo desenvolver uma ferramenta computacional capaz de realizar previsões de séries temporais, baseada na teoria de Sistemas de Inferência Fuzzy, em conjunto com a otimização de parâmetros por Algoritmos Genéticos, oferecendo uma interface gráfica intuitiva e amigável.
The time series forecasting is present in several areas such as electrical, financial, economy and industry. In all these areas, the forecasts are critical to decision making in the short, medium and long term. Certainly, statistical techniques are most often used in time series forecasting problems, mainly because of a greater degree of interpretability, guaranteed by the mathematical models generated. However, computational intelligence techniques have been increasingly applied in time series forecasting in academic research, with emphasis on Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS). There are many cases of successful application of ANNs, but the systems developed are black box, not allowing a better understanding of the final prediction. On the other hand the FIS are interpretable, but its application is compromised by reliance on rule-making by experts and by the difficulty in adjusting the various parameters as the number and shape of fuzzy sets and the window size. Moreover, the lack of people with the knowledge necessary for the development and use of models based on these techniques also restricts their application in the routine planning and decision making in most organizations. This work aims to develop a computational tool able to make forecasts of time series, based on the theory of Fuzzy Inference Systems, in conjunction with the optimization of parameters by Genetic Algorithms, providing an intuitive and friendly graphical user interface.

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Page, Alison L. 1971. "Forecasting mix-sensitive semiconductor fabrication tool set requirements under demand uncertainty." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/84517.

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Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2001.
Includes bibliographical references (leaves 74-75).
by Alison L. Page.
S.M.
M.B.A.

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Watkiss, Brendon Miles. "The SLEUTH urban growth model as forecasting and decision-making tool." Thesis, Stellenbosch : Stellenbosch University, 2008. http://hdl.handle.net/10019.1/1654.

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Thesis (MSc (Geography and Environmental Studies))--Stellenbosch University, 2008.
Accelerating urban growth places increasing pressure not only on the efficiency of infrastructure and service provision, but also on the natural environment. City managers are delegated the task of identifying problem areas that arise from this phenomenon and planning the strategies with which to alleviate them. It is with this in mind that the research investigates the implementation of an urban growth model, SLEUTH, as a support tool in the planning and decision making process. These investigations are carried out on historical urban data for the region falling under the control of the Cape Metropolitan Authority. The primary aim of the research was to simulate future urban expansion of Cape Town based on past growth patterns by making use of cellular automata methodology in the SLEUTH modeling platform. The following objectives were explored, namely to: a) determine the impact of urbanization on the study area, b) identify strategies for managing urban growth from literature, c) apply cellular automata as a modeling tool and decision-making aid, d) formulate an urban growth policy based on strategies from literature, and e) justify SLEUTH as the desired modeling framework from literature. An extensive data base for the study area was acquired from the product of a joint initiative between the private and public sector, called “Urban Monitoring”. The data base included: a) five historical urban extent images (1977, 1988, 1993, 1996 and 1998); b) an official urban buffer zone or ‘urban edge’, c) a Metropolitan Open Space System (MOSS) database, d) two road networks, and d) a Digital Elevation Model (DEM). Each dataset was converted to raster format in ArcEdit and finally .gif images were created of each data layer for compliance with SLEUTH requirements. SLEUTH processed this historic data to calibrate the growth variables for best fit of observed historic growth. An urban growth forecast was run based on the calibration parameters. Findings suggest SLEUTH can be applied successfully and produce realistic projection of urban expansion. A comparison between modelled and real urban area revealed 76% model accuracy. The research then attempts to mimic urban growth policy in the modeling environment, with mixed results.

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Palmer, Jeffrey M. "Incorporating ensemble-based probabilistic forecasts into a campaign simulation in the Weather Impact Assessment Tool (WIAT)." Thesis, Monterey, California : Naval Postgraduate School, 2010. http://edocs.nps.edu/npspubs/scholarly/theses/2010/Jun/10Jun%5FPalmer.pdf.

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Thesis (M.S. in Meteorology and Physical Oceanography)--Naval Postgraduate School, June 2010.
Thesis Advisor: Stone, Rebecca. ; Second Reader: Durkee, Philip. "June 2010." Description based on title screen as viewed on July 16, 2010. Author(s) subject terms: Stochastic forecasting, probabilistic forecasting, operational simulation. Includes bibliographical references (p. 115-116). Also available in print.

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Bartholomew, Nathan. "Accurately predicting visitation as a strategic tool for management of a public park." Thesis, Kansas State University, 2017. http://hdl.handle.net/2097/35445.

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Master of Agribusiness
Department of Agricultural Economics
Nathan P. Hendricks
Public parks can provide considerable value to the population that visit them, for the community around them and the local economy. A well designed public park can attract growth in tourism, stimulate a habitat for wildlife, contribute to personal health and wellness, improve the aesthetics of an area and stimulate economic growth. Managing and operating a public park entails many complex issues such as designing an attractive green space, implementing and maintaining the park, attracting and managing visitors and obtaining financial support. Public parks need to identify factors that influence park visitation in order to more effectively manage park visitorship.. This thesis examines park visitation analyzing data of park users of The High Line in New York City to develop a model to more accurately predict visitation. The thesis focuses on the critical social and climatic variables that attract visitors to spend time in the High Line park. Understanding these factors will allow park management the ability to create a strategic plan for managing a public space that best serves its visitors and the community. More specifically, a strategic plan helps to determine who the visitors are and what activities they enjoy in the park. In conceptualizing a solution, High Line can put into practice what its visitors want to see offered in the park and which of its programming needs improvement to attract more visitors. Meeting the needs of park visitors will create a better experience for the customers and a better management strategy for operations. A multivariate regression analysis was used to establish the relationship between High Line visitation and the climatic and social variables. The climatic variables of daily average temperature and precipitation. The social variables of day of the week and season of the year were added to the structural model as dummies. A time trend variable characterized as time in years was added to the model to show any yearly change in visitation to the park. This method has been widely applied to a number of studies testing the relationship of climatic and social variables to park visitation (Micah, Scotter and Fenech 2016). The results of this regression analysis show that the social variables of day of the week and season and the climatic variables of average temperature and precipitation had a significant affect on park visitation. The model developed can be used to forecast park visitation, quantifying the many variables that influence park visitation.

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Margolis, Michael C. "Upgradable operational availability forecasting tool for the U.S. Navy P-3 replacement aircraft." Thesis, Monterey, California. Naval Postgraduate School, 2003. http://hdl.handle.net/10945/6298.

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Approved for public release; distribution in unlimited.
The P-3 Orion maritime aircraft has been the U.S. Navy's primary maritime patrol aircraft since its fleet introduction in 1962. Naval Aviation Systems Command (NAVAIR) has determined that the P-3 fleet has sufficiently aged to warrant a replacement. The replacement aircraft is currently undergoing the conceptual phase of development and it is during this period that NAVAIR is interested in evaluating the trade-off between operational availability and the associated cost to achieve this operational availability. This thesis developed a simulation tool that was used to investigate relationships that affect cost and operational availability of the new (notional) aircraft on a deployment. The simulation tool was exercised for select scenarios in order to gain insights into the value of investing funds in additional aircraft versus the value of investing funds in increased component reliability. The simulation was developed to be very flexible and extensible, enhancing its value for future analyses. Required data inputs into the simulation tool are formatted utilizing a new technology called Extensible Markup Language (XML) which facilitates use of the data in nearly all computer software packages. The model is robust in nature and can be applied to a wide variety of aircraft.

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Motamarri, Srinivas. "Development of a Neural Based Biomarker Forecasting Tool to Classify Recreational Water Quality." University of Cincinnati / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1291307369.

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Margolis, Michael C. "Upgradeable operational availability forecasting tool for the U.S. Navy P-3 replacement aircraft /." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2003. http://library.nps.navy.mil/uhtbin/hyperion-image/03sep%5FMargolis.pdf.

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Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 2003.
Thesis advisor(s): Arnold H. Buss, David A. Schrady. Includes bibliographical references (p. 107-108). Also available online.

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Budd, David A. "Characterising volcanic magma plumbing systems : A tool to improve eruption forecasting at hazardous volcanoes." Doctoral thesis, Uppsala universitet, Mineralogi, petrologi och tektonik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-267473.

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This thesis attempts to develop our understanding of volcanic magma plumbing systems and the magmatic processes that operate within them, such as fractional crystallisation, crustal partial melting, assimilation, and magma mixing. I utilise petrology, rock and mineral geochemistry, and isotope systematics to seek to improve our ability to forecast the eruptive frequency and style of active volcanoes, an aspect often lacking in current volcano monitoring efforts. In particular, magma reservoir dynamics are investigated from a mineral scale at Katla volcano in Iceland, to a sub-mineral scale at Merapi, Kelud, and Toba volcanoes in Indonesia. The magma plumbing architecture of Katla volcano on Iceland is explored in the first part of this thesis. Crystalline components within tephra and volcanic rock preserve a record of the physical and chemical evolution of a magma, and are analysed through oxygen isotopic and thermobarometric techniques to temporally constrain changes in reservoir depth and decode the petrogenesis of the lavas. We find both prolonged upper crustal magma storage and shallow level assimilation to be occurring at Katla. The results generated from combining these analytical strands reveal the potential for unpredictable explosive volcanism at this lively Icelandic volcano. The second part of this thesis examines the magma plumbing systems of Merapi, Kelud and Toba volcanoes of the Sunda arc in Indonesia at higher temporal and petrological resolution than possible for Katla (e.g., due to the crystal poor character of the rocks). For this part of the thesis, minerals were analysed in-situ to take advantage of sub-crystal scale isotopic variations in order to investigate processes of shallow-level assimilation in the build-up to particular eruptions. We find that intra-crystal analyses reveal an otherwise hidden differentiation history at these volcanoes, and establish a better understanding as to how they may have rapidly achieved a critical explosive state. The outcomes of this thesis therefore deepen our knowledge of evolutionary trends in magma plumbing system dynamics, and highlight the importance of understanding the geochemical processes that can prime a volcano for eruption. Lastly, I emphasise the vital contribution petrology can make in current volcano monitoring efforts.

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Smith, Rosanna. "Rates of rock fracturing as a tool for forecasting eruptions at andesitic-dacitic stratovolcanoes." Thesis, University College London (University of London), 2008. http://discovery.ucl.ac.uk/1445117/.

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Increasing rates of volcano-tectonic (VT) seismicity, produced by rock fracture and slip along faults, are a common precursor to eruptions. Precursory VT seismicity can thus be related to how fractures develop within and below a volcano before it erupts. This study combines field and experimental data to define constraints on theoretical models for accelerating VT seismicity. VT seismicity before all 17 episodes of lava-dome growth at Mount St. Helens between 1980 and 1986 and before eruptions at selected andesitic-dacitic volcanoes following more than a century of repose was analysed. VT precursors developed within three weeks of lava-dome growth episodes, with stronger patterns before eruptions through larger domes, suggesting that the domes themselves inhibited magma ascent. The accelerations fluctuated about mean trends between exponential and hyperbolic, suggesting that individual sequences evolved under different boundary conditions, including applied stress and rock temperature, that determine the rates of seismogenic fracturing. Before the first eruption after a long repose interval, a hyperbolic acceleration in VT seismicity developed over approximately ten days when the eruption was dome building rather than phreatomagmatic. To investigate the effect of changing boundary conditions, samples of andesite were deformed in compression at temperatures up to 900 °C and confining pressures up to 50 MPa with acoustic emissions (AE) recorded as analogues to VT events. There was no temperature or pressure dependence in mechanical properties nor AE precursors to sample failure at temperatures up to 600 °C for all confining pressures tested. This supports the use of models of precursory VT seismicity based on brittle fracture for volcanoes erupting after long repose intervals, where a new magmatic pathway must be formed. High AE rates for samples tested at 900 °C, which is within the brittle-ductile transition, indicate that VT events can originate from hot material within the lava dome and at magma conduit margins.

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Hunter, Bruce Allan. "A geospatial tool for assessing potential wildland fire risk in central Texas." Thesis, University of North Texas, 2005. https://digital.library.unt.edu/ark:/67531/metadc4870/.

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Wildland fires in the United States are not always confined to wilderness areas. The growth of population centers and housing developments in wilderness areas has blurred the boundaries between rural and urban. This merger of human development and natural landscape is known in the wildland fire community as the wildland urban interface or WUI, and it is within this interface that many wildland fires increasingly occur. As wildland fire intrusions in the WUI increase so too does the need for tools to assess potential impact to valuable assets contained within the interface. This study presents a methodology that combines real-time weather data, a wildland fire behavior model, satellite remote sensing and geospatial data in a geographic information system to assess potential risk to human developments and natural resources within the Austin metropolitan area and surrounding ten counties of central, Texas. The methodology uses readily available digital databases and satellite images within Texas, in combination with an industry standard fire behavior model to assist emergency and natural resource managers assess potential impacts from wildland fire. Results of the study will promote prevention of WUI fire disasters, facilitate watershed and habitat protection, and help direct efforts in post wildland fire mitigation and restoration.

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Abrahams, Shaheed. "Budgeting, forecasting and financial planning as a strategic tool in the Eastern Cape's manufacturing industry." Thesis, Nelson Mandela Metropolitan University, 2012. http://hdl.handle.net/10948/d1008408.

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The primary objective of the study is to assess whether organisations are using their budgeting, forecasting and financial planning information as a strategic tool in the decision-making process. The research aims to investigate the various factors that hinder the success of the finance department in delivering a quality financial plan, budget or forecast to top management and the rest of the organisation.

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Sutterer, Lucas B. (Lucas Benjamin). "Development of a tool for forecasting a warehouse facility footprint and enabling rapid scenario analysis." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/59186.

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Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 60).
Companies in every industry, including both manufacturers and service providers, must make decisions about their operational footprint -the amount of building space required for business needs such as storing inventory and equipment and providing work areas for employees. Changes to the existing footprint often involve buying, building, expanding, leasing or selling facilities. These are long lead time decisions, making it critical to accurately forecast these needs far in advance. The problem is that many companies do not know what facility footprint requirements will be years from now. This thesis addresses the problem by investigating factors that drive space requirements and estimating trends, resulting in a five year space forecast. An approach is provided for quantifying a proactive outlook, thereby enabling more confident decisions regarding the operational footprint of the future. The thesis addresses how to adapt the forecast to create a valuable instrument that enables analysis of changing conditions and assumptions in a dynamic environment. -This provides the ability to easily and intuitively compare the outcome of multiple changes with one another. It also displays the capacity to perform analysis of complex multivariable scenarios. We explore in this thesis approaches for reducing facility size required to store inventory. These approaches include consolidation of warehouses, utilization of high bay storage and the identification and elimination of aging inventory. This research was conducted at Raytheon Company, a US-based defense contractor, with a focus on predicting warehouse space required to store inventory to support their manufacturing operations. However, these concepts apply to any situation where costly investments must be made to enable capacity to meet demand. This includes expansion or contraction of manufacturing plants, retail stores and office buildings. A proactive approach enables more insightful decisions about capital investment, construction plans and lease terms.
by Lucas B. Sutterer.
S.M.
M.B.A.

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KUMAR, NEERAJ. "DESIGNING OF MARKET MODEL, EFFECTIVE PRICE FORECASTING TOOL AND BIDDING STRATEGY FOR INDIAN ELECTRICITY MARKET." Thesis, DELHI TECHNOLOGICAL UNIVERSITY, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18910.

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The Development scenario for renewable energy across the globe is changing rapidly in terms of capacity addition and grid interconnection. Penetration of renewable energy resources into grid is necessary to meet the elevated demand of electricity. In view of this penetration of solar and wind power growing enormously across the globe. Solar energy is widely escalating in terms of generation and capacity addition due its better predictability over wind energy. Electricity pricing is one of the important aspects for power system planning and it felicitates information for the electricity bidder for exact electricity generation and resource allocation. The important task is to forecast the electricity price accurately in grid interactive environment. This task is tedious in renewable integrated market due to intermittency issue. As renewable energy penetration into the grid is enhancing swiftly. An appropriate market model addressing the issues of related to renewable energy specially wind and solar is necessary. A novel solar energy-based market model is proposed for state level market along with the operating mechanism. The different component associated with grid and their functionality in the operation of grid is discussed. Challenges and possible solutions are addressed to implement the market model. Energy trading plays a crucial role in the economic growth of country. Renewable energy trading opens a new avenue for the economic growth. India is blessed with a rich solar energy resources, the solar power producers tapped the potential of solar up to appreciable extent, but due to lack of trading models and specific regulatory mechanism in context of renewable energy generation is main hurdle in competition among generators. Various market model developed for solar energy trading at state level electricity along with their trading mechanism is presented. Also features of the models are also addressed. xiii A Rigorous literature review on price forecasting is conducted with focus on impact of solar and wind energy on electricity price. The data of Australia electricity market is collected for price forecasting. The correlation among the inputs for price is calculated using correlation coefficient formula and selected the highly corelated input with price. Artificial Neural Network (ANN) is implemented to forecast the price by using historical data. The price is predicted for January to June month and weekly forecast of price for the same month is executed. The minimum MAPE is 1.94 for April month and 1.03 for third week of January. The research work is continued to investigate the impact of solar and wind energy on electricity price. The Long short-term memory (LSTM) is designed to forecast the electricity price considering the solar power penetration. The raw data of Austria market consists of actual day ahead load, forecasted day ahead load, actual day ahead price and actual solar generation is used. The reliability of forecasting model is analyzed by computation of confidence interval on MAPE. The research work is extended to investigate the impact of wind energy on electricity price. The Austria electricity market data is used for investigating the potential impact of wind energy on rice. The statistical analysis of the data is conducted for finding the suitability of the model. Decision tree model is designed and implemented and significant reduction in the forecasting accuracy of 5.802 is achieved for the data set using wind energy as input parameter. The future of solar energy in India is positive. The growth of solar energy in terms of capacity addition and grid interconnection programme is expanding day by day. To promote the solar energy trading in open market a suitable bidding mechanism must be designed for solar power producers. It becomes pertinent to design the bidding strategy for solar power producers to maximize their profit considering the uncertainty in the energy output. Hybrid Particle Swarm Optimization – Gravitational Search Algorithm (HPSO - GSA) is proposed for designing the optimal bidding strategy for solar PV power producer for designed solar energy xiv based Indian electricity market. The objective function is designed considering the constraint of uncertainty and energy imbalance in price. The proposed algorithm shows highest profit when compared with Real Coded Genetic Algorithm (RCGA), Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). In the light of continual renewable energy growth and grid interconnection, a novel solar energy-based electricity market model addressing the issues of solar energy is proposed to make the system effective and reliable. This novel market may fill the promise of providing electricity at competitive cost for all in India. The various market models are proposed for trading the solar energy in competitive market for maximum utilization of untapped potential of solar energy. The various trading models may be implemented based on the application and suitability. The electricity price forecasting is an important aspects of power system planning and for renewable energy interactive grid price forecasting is crucial task due its intermittent nature. ANN model is proposed for price forecasting and significant improvement in MAPE is reported for Australia electricity market data. Further the investigation has been done on the impact of solar energy generation on electricity price using machine learning techniques (DT, RF, LASSO, XGBOOST and LSTM). The LSTM model accuracy is good in price forecasting with consideration of solar energy as input parameter. The investigation is extended for impact of wind energy on electricity price and Decision tree model accuracy is superior as compared to RF, LASSO, LR, SVR and DNN model. The bidding strategy for the designed solar based electricity model is proposed using HPSO-GSA method and profit calculation has been done for solar PV producers on real time data. The maximized profit has been obtained through HSPO-GSA method for two different sets of datasets.

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Rajagopal, Seshadri. "Development and evaluation of a streamflow forecasting tool to improve reclamation operational water supply forecasts in the Carson River /." abstract and full text PDF (free order & download UNR users only), 2006. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1440929.

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Thesis (M.S.)--University of Nevada, Reno, 2006.
"Fall, 2006." Includes bibliographical references (leaves 66-67). Online version available on the World Wide Web. Library also has microfilm. Ann Arbor, Mich. : ProQuest Information and Learning Company, [2006]. 1 microfilm reel ; 35 mm.

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Khomo, Melvin Muzi. "The yield curve as a forecasting tool : does the yield spread predict recessions in South Africa?" Thesis, Rhodes University, 2006. http://hdl.handle.net/10962/d1004722.

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This paper examines the ability of the yield curve to predict recessions in South Africa, and compares its predictive power with other commonly used variables that include the growth rate in real money supply, changes in stock prices and the index of leading economic indicators. The study also makes an attempt to find out if monetary policy explains the yield spread's predictive power with regards to future economic activity. Regarding methodology, the standard probit model proposed by Estrella and Mishkin (1996) that directly estimates the probability of the economy going into recession is used. Results from this model are compared with a modified probit model suggested by Dueker (1997) that includes a lagged dependent variable. Results presented in the paper provide further evidence that the yield curve, as represented by the yield spread between 3-month and IO-year government paper, can be used to estimate the likelihood of recessions in South Africa. The yield spread can produce recession forecasts up to 18 months, although it's best predictive power is seen at two quarters. Results from the standard probit model and the modified pro bit model with a lagged dependent variable are somewhat similar, although the latter model improves forecasts at shorter horizons up to 3 months. Compared with other indicators, real M3 growth is a noisy indicator and does not provide much information about future recessions, whilst movements in the All-Share index can provide information for up to 12 months but does not do better than the yield curve. The index of leading economic indicators outperforms the yield spread in the short run up to 4 months but the spread performs better at longer horizons. Based on the results from the study, it appears that changes in monetary policy explain the yield spread's predictive power. This is because the yield spread loses its explanatory power when combined with a variable representing the monetary policy stance of the central bank.

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Molinar, Torres Gabriela Alejandra [Verfasser]. "Machine Learning Tool for Transmission Capacity Forecasting of Overhead Lines based on Distributed Weather Data / Gabriela Alejandra Molinar Torres." Karlsruhe : KIT-Bibliothek, 2020. http://d-nb.info/1223985873/34.

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Tong, Fan. "Capacity demand and climate in Ekerö : Development of tool to predict capacity demand underuncertainty of climate effects." Thesis, KTH, Elektroteknisk teori och konstruktion, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-152522.

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The load forecasting has become an important role in the operation of power system, and several models by using different techniques have been applied to solve these problems. In the literature, the linear regression models are considered as a traditional approach to predict power consumption, and more recently, the artificial neural network (ANN) models have received more attention for a great number of successful and practical applications. This report introduces both linear regression and ANN models to predict the power consumption for Fortum in Ekerö. The characteristics of power consumption of different kinds of consumers are analyzed, together with the effects of weather parameters to power consumption. Further, based on the gained information, the numerical models of load forecasting are built and tested by the historical data. The predictions of power consumption are focus on three cases separately: total power consumption in one year, daily peak power consumption during winter and hourly power consumption. The processes of development of the models will be described, such as the choice of the variables, the transformations of the variables, the structure of the models and the training cases of ANN model. In addition, two linear regression models will be built according to the number of input variables. They are simple linear regression with one input variable and multiple linear regression with several input variables. Comparison between the linear regression and ANN models will be carried out. In the end, it finds out that the linear regression obtains better results for all the cases in Ekerö. Especially, the simple linear regression outperforms in prediction of total power consumption in one year, and the multiple linear regression is better in prediction of daily peak load during the winter.

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Silva, Henderson Amparado de Oliveira. "Power Map Explorer: uma ferramenta para visualização e previsão de vazões." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-11122007-140030/.

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A complexidade inerente ao processo de produção de energia apresenta um desafio aos especialistas quando estes se deparam com o dimensionamento e operação de sistemas de recursos hídricos. A produção energética de um sistema hidroelétrico depende fundamentalmente das séries de vazões afluentes às diversas usinas hidrelétricas do sistema. No entanto, a incerteza das vazões futuras e sua aleatoriedade são obstáculos que dificultam todo o planejamento da operação do sistema energético brasileiro. A inexistência de um software específico para análise de séries de vazões ocorridas nas usinas hidrelétricas, associada à importância desse tipo de dado no contexto energético, motivou a concepção de uma ferramenta gráafica para visualização e previsão desses dados. Acredita-se que a visualização desses dados por meio de representações apropriadas e altamente interativas possa promover hipóteses e revelar novas informações dos fenômenos associados a essas quantidades, melhorando a qualidade das decisões de planejamento do sistema energético. Este trabalho de mestrado apresenta em detalhes o sistema desenvolvido, chamado Power Map Explorer, e das técnicas nele implementadas
The complexity inherent to the process of energy production introduces a challenge to the experts when they are faced with dimension and operation of water resources systems. The energy production of a hidroeletric system depends on streamflow time series from hydroelectric plants located on different rivers of the system. However, the uncertainty and randomness of future streamflow series impose difficulties to the planning and operation of the brazilian energy system. The lack of a software suite to support the analysis of inflow series from hydroelectric plants, and the importance of this data in the energy context motivated the conception and implementation of a graphical tool to visualize and forecast this type data. The appropriate level of visualization and interaction with this type of data can spring new hypotheses and reveal new information, leading to performance improvement of the task of energetic planning. This work presents a software for visualization and forecast of inflow data series, the Power Map Explorer, in detail

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Butler, Melody Nicole. "An assessment tool for the appropriateness of activity-based travel demand models." Thesis, Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/45948.

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As transportation policies are changing to encourage alternative modes of transportation to reduce congestion problems and air quality impacts, more planning organizations are considering or implementing activity-based travel demand models to forecast future travel patterns. The proclivity towards operating activity-based models is the capability to model disaggregate travel data to better understand the model results that are generated with respect to the latest transportation policy implementations. This thesis first examines the differences between the two major modeling techniques used in the United States and then describes the assessment tool that was developed to recommend whether a region should convert to the advanced modeling procedures. This tool consists of parameters that were decided upon based on their known linkages to the advantages of activity-based models.

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Almamy, Jeehan. "An evaluation of Altman's Z score using cash flow ratio as analytical tool to predict corporate failure amid the recent financial crisis in the UK." Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/13735.

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One of the most important threats for many firms today, despite their nature of the operation, size and longevity, is insolvency. Existing empirical evidence has shown that in the past two decades, business failures have occurred at a higher rate than any time since the 1930s. Many business failure studies have been conducted over time using financial ratios as inputs and traditional statistical techniques. Some of these studies examined whether cash flow information improves the prediction of business failure. Most recently, researchers have employed discriminant analysis to perform business failure prediction. The recent changes in the world caused by unstable environments where many firms fail more than ever, there is increasing need to predict business failure. To this date, there have been limited previous studies conducted on failure prediction for UK firms. Even in other countries, there has been a small amount of research done in the field of firm failures. Therefore, this study investigates the extension of Altman’s (1968) original model in predicting the health of UK firms using discriminant analysis and performance ratios to test which ratios are statistically significant in predicting the health of the UK firms .a selected sample containing 90 failed and 1000 non failed on UK industrial firms from 2000 – 2013. The main purpose of this study is to contribute towards Altman’s (1968) original Z-score model by adding new variables (Cash flow ratio). The study found that cash flow, when combined with Altman’s original variables is highly significant in predicting the health of UK general firms. A J-UK model was developed to test the health of UK firms. When compared with the re-estimated the Altman’s original model in the UK context, the predictive power of the model was 82.9%, which is consistent with Taffler’s (1982) UK model. Furthermore, to test the predictive power of the model before, during and after the financial crisis periods; results show that J-UK model had a higher accuracy to predict the health of UK firms than the re-estimated Altman’s original model. Finally, the study proves that liquidity, profitability, leverage and capital turnover ratios are significant ratios in predicting failure. Liquidity and profitability have the highest contribution to the results of both re-estimated Altman’s original model and J-UK model. This study has implications for decision makers. Regulatory bodies and practitioners have to take into account the ratios, which contributed highest to the model in order to serve as early warning signals for corrective action.

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Lind, Rutger, and Johan Törnblad. "Identification and Analysis of Market Indicators : a predictive tool for anticipating future demand fluctuations on the telecom mobile network equipment market." Thesis, Linköping University, Department of Management and Economics, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1107.

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Background: Forecasting is an instrument that the managers rely upon for their anticipations of the future. Subcontractors control their operations according to the forecast volumes provided by the telecom mobile network equipment suppliers. The information in the forecasts is however not sufficient.

Purpose: The purpose of this thesis is to identify and test relevant and available market indicators for prediction of future demand fluctuations on the telecom mobile network equipment market.

Realisation: During a number of interviews, factors that are driving the network equipment market were clarified. The aim of this part was to identify possible market indicators. Hypotheses were set up to test the chosen indicators. In the second part, the indicators were tested statistically. Finally, the theoretical and logical support of the results was discussed.

Result: To predict future movements in network equipment demand, the market indicators should focus on the telecom mobile operators, and their ability, need, and willingness to make new investments. The market indicators proven to be of most importance after the regression analyses were long-term market interest rates and telecom corporate bond indices.

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IbaÌnÌƒez, Juan-Carlos. "New tools for multi-step forecasting of nonlinear time series." Thesis, Lancaster University, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.435881.

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Fortune, Christopher Joseph. "Factors affecting the selection of building project price forecasting tools." Thesis, Heriot-Watt University, 1999. http://hdl.handle.net/10399/1271.

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This thesis contributes to what is known about the investigation and formulation phases of the building project price forecasting advice process. The research has developed a greater understanding of what general factors affect the selection of non-traditional types of building project price forecasting models. The thesis adopted a two-phased combined research approach. The first phase required a population mailed survey to be executed with over two thousand three hundred quantity surveying organisations located across England in 1997. The second phase required thirty-one in-depth interviews to be executed, with informed practitioners, in five rounds of data collection. Consequently, this research firstly, established the types of building project price forecasting models or tools in-use in England. The study found that the called for paradigm shift away from the traditional types of models, had not yet been generally achieved. The study provided evidence that some types of quantity surveying organisations were moving towards the adoption of the non-traditional models, for use as additional tools. The study then, secondly, identified a number of general factors that were found to affect the selection of non-traditional types of building project price forecasting models. The thesis concluded by generating a grounded constraints-based theory of factors found to affect the selection of non-traditional types of building project price forecasting models. The emergent theory identified the parameters needed to enable all types of quantity surveying organisations to become involved with the selection of non-traditional models or tools.

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Motsomi, Abel Pholo. "Statistical tools for consolidation of energy demand forecasts." Thesis, Nelson Mandela Metropolitan University, 2012. http://hdl.handle.net/10948/d1011578.

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The electricity market in the South African economy uses specialised instruments in forecast-ing the energy load to be delivered. The current status quo operates with several forecasters from different offices, departments or businesses predicting for different purposes. This be-comes a challenge to derive a consolidated forecast. This study has attempted to develop a consolidating instrument that will merge all the forecasts from different offices, departments or businesses into one so-called ‘official forecast’. Such an instrument should be able to predict with accuracy the anticipated usage or demand. Article [18] examined patterns across G7 countries and forecasters to establish whether the present bias reflects the inefficient use of information, or whether it reflects a rational re- sponse to financial, reputation and other incentives operating for forecasters. This bias is particularly true for any electricity utility as forecasting is undertaken by different divisions; therefore each division has its own incentives. For instance, the generation division will tend to overstate their forecasts so as that there is no possibility of a shortage, whereas distri- bution (sales) might understate so as to give the impression of being profitable when more units are sold to consumers. Thus, the study attempts to rectify this bias by employing statistical tools in consolidating these forecasts. The results presented in this paper propose a newly developed procedure of consolidating energy demand forecasts from different users and accounting for different time horizons. Predicting for the short-term and long-term involves different measuring tools, which is one aspect of prediction this paper tackles.

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FARIAS, DOUGLAS ALEXANDER ALVES DE. "DAILY ELECTRICITY FORECASTING IN LOAD LEVELS, COMBINING STATISTICAL AND COMPUTATIONAL INTELLIGENCE TOOLS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2008. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=13211@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
OPERADOR NACIONAL DO SISTEMA ELÉTRICO
Esta dissertação apresenta um estudo sobre o comportamento da carga de energia agregada em intervalos temporais dentro de um mesmo dia. Esse tipo de agregação já vem sendo utilizado no setor elétrico brasileiro, sob a forma de três patamares de carga, denominados leve, média e pesada. No entanto, tais patamares são sempre obtidos indiretamente, a partir da agregação da carga horária, não tendo sido encontrado, até a publicação dessa dissertação, nenhum tratamento de forma direta dos mesmos. O trabalho desenvolvido na dissertação descreve matematicamente o cálculo dos três patamares de carga e faz uma análise das séries dessas variáveis, verificando suas características próprias, relações entre si e a influência de variáveis exógenas. Apresenta, também, a modelagem de alguns métodos de previsão para essas séries, empregando técnicas tanto estatísticas quanto de inteligência computacional e propõe um modelo híbrido de previsão, combinando regressão dinâmica, classificador de padrões, lógica nebulosa e um método para combinar os padrões. No modelo proposto, a regressão dinâmica é empregada na previsão da carga diária global, usada para adequar os perfis, descritos de forma normalizada, aos níveis reais das séries. Os perfis são obtidos a partir de um classificador de padrões baseado na técnica subtractive clustering. A combinação dos perfis, que compõem a previsão dos patamares para o horizonte desejado, é feita por um sistema de lógica nebulosa, que usa a temperatura como variável de entrada, tratando de forma intrínseca relações não lineares entre essas variáveis, e um método que trata a saída do sistema nebuloso de forma empírica.
This dissertation presents a study of electricity load aggregated in time intervals into the same day. This type of aggregation has been used by the Brazilian´s electrical sector in the form of three load levels called low, middle and high. However, these load levels were always indirectly achieved from the hourly load aggregation, and it was not found any direct treatment of them as a series up to this publication. The work developed in this dissertation describes mathematically the calculation of the three levels of load and makes an analysis of the series formed by these variables checking their own characteristics, the relationship among themselves and the influence of exogenous variables. It also shows the modeling of some forecast methods for such series employing techniques of both statistics in computational intelligence, introduces the level profile concept and proposes a hybrid model of forecasting, formed by dynamic regression, pattern classification and fuzzy logic, to predict the load level pattern. In the proposed model, the dynamic regression is used in the forecasting of the daily global load that is used to match the resulting pattern, described in a normalized way to the actual load values. The profiles are obtained from a classifier based on the subtractive clustering technique. The combination of the profiles that compose the level pattern forecast to the desired horizon is carried out by a fuzzy logic system that uses the temperature as input variable intrinsically treating non-linear relationships between load level and temperature variables.

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Di, Nicola Francesca <1980&gt. "Urban air quality: new high-resolution modeling approaches and forecasting tools for citizens." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amsdottorato.unibo.it/10254/1/DiNicola_Francesca_Tesi.pdf.

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Air pollution is one of the greatest health risks in the world. At the same time, the strong correlation with climate change, as well as with Urban Heat Island and Heat Waves, make more intense the effects of all these phenomena. A good air quality and high levels of thermal comfort are the big goals to be reached in urban areas in coming years. Air quality forecast help decision makers to improve air quality and public health strategies, mitigating the occurrence of acute air pollution episodes. Air quality forecasting approaches combine an ensemble of models to provide forecasts from global to regional air pollution and downscaling for selected countries and regions. The development of models dedicated to urban air quality issues requires a good set of data regarding the urban morphology and building material characteristics. Only few examples of air quality forecast system at urban scale exist in the literature and often they are limited to selected cities. This thesis develops by setting up a methodology for the development of a forecasting tool. The forecasting tool can be adapted to all cities and uses a new parametrization for vegetated areas. The parametrization method, based on aerodynamic parameters, produce the urban spatially varying roughness. At the core of the forecasting tool there is a dispersion model (urban scale) used in forecasting mode, and the meteorological and background concentration forecasts provided by two regional numerical weather forecasting models. The tool produces the 1-day spatial forecast of NO2, PM10, O3 concentration, the air temperature, the air humidity and BLQ-Air index values. The tool is automatized to run every day, the maps produced are displayed on the e-Globus platform, updated every day. The results obtained indicate that the forecasting output were in good agreement with the observed measurements.

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Eshete, Getachew. "Assessment of fuelwood resources in acacia woodlands in the Rift Valley of Ethiopia : towards the development of planning tools for sustainable management /." Umeå : Swedish Univ. of Agricultural Sciences (Sveriges lantbruksuniv.), 1999. http://epsilon.slu.se/avh/1999/91-576-5638-X.pdf.

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Ritchey, Chris D. "Analysis and evaluation of forecasting methods and tools to predict future demand for secondary chemical-biological configuration items." Monterey, California: Naval Postgraduate School, 2013. http://hdl.handle.net/10945/34729.

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Approved for public release; distribution is unlimited
As the Engineering Support Activity (ESA) for numerous consumable Chemical Biological items managed by the Defense Logistics Agency (DLA), Edgewood Chemical Biological Center (ECBC) must be able to complete reviews of all procurement packages within 15 calendar days. With such little lead time, it would be very beneficial if ECBC had the ability to forecast when DLA procurement actions will occur. This thesis presents an evaluation of the effectiveness of Simple Regression and Exponentially Weighted Moving Average (EWMA) forecasting models to predict the demand of Chemical Biological consumable items using the procurement history data for four specific items. Neither forecasting model proved effective at predicting the demand for the items due in large part to large variation in demand patterns. The inventory policies and supply issues which currently exist at an Army production site were investigated and it was recommended to consider Economic Order Quantity (EOQ) or Just-in-Time (JIT) inventory management models as possible alternatives to achieve smoother demand patterns. Additionally, recommendations were made to examine the integrity of the historical demand data as well as using a Multiple Regression forecast model with several causal effects in addition to time.

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Григорян, Т. Г. "Моделі та інструменти прогнозування цінності в проектах створення нових продуктів." Thesis, Сумський державний університет, 2016. http://essuir.sumdu.edu.ua/handle/123456789/46530.

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Створення нового продукту, яке включає в себе процеси проектування, виготовлення і експлуатації, є яскравим прикладом програмного та проектного управління. Одним із завдань, що повинно бути вирішено при створенні нового продукту і виведенні його на ринок, є задоволення очікувань зацікавлених сторін, включаючи спонсорів і майбутніх користувачів. Ключовим параметром, що характеризує задоволеність зацікавлених сторін проекту, є цінність його продукту.

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Tysyachnaya, Yunna. "Information tools of modeling and forecasting the state of the territory of ukraine according to the level of environmental protection." Thesis, Видавництво СумДУ, 2011. http://essuir.sumdu.edu.ua/handle/123456789/10264.

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Ukrainets, I., and N. Karaeva. "Information tools of modeling and forecasting the state of the territory of ukraine according to the level of environmental protection." Thesis, Видавництво СумДУ, 2011. http://essuir.sumdu.edu.ua/handle/123456789/10275.

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Чуба, В. О. "Інструментарій прогнозування банківських криз." Thesis, Сумський державний університет, 2019. https://essuir.sumdu.edu.ua/handle/123456789/77687.

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Діяльність кожного банку як незалежного суб’єкта банківського сектору взаємопов’язана з ризиком, що обумовлено головним завданням їхньої діяльності – отримання максимального прибутку. Відповідно, суттєвим завданням для забезпечення стабільності банківського сектору є дослідження та розробка інструментів для прогнозування кризових тенденцій. Вивчення даного напрямку повинно орієнтуватися на забезпечення економічної стабільності держави, оскільки поява кризових процесів в банківському секторі, часто зменшує можливості та перспективи для стабільного економічного зростання. Світовий та вітчизняний досвід вказує на необхідність розробки та використання ефективної системи прогнозування банківських криз.

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Beckman, Fanny, and Cilano Sofie Munke. "Foresight Triangulation - Ett innovativt stöd för att tolka framtiden : En zombielista för år 2026." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-49074.

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Studien påvisar att en trianguleringsmetod för att utföra foresight på ett resurseffektivt sätt går att tillämpa. Den framtagna metoden Foresight Triangulation gav en träffsäkerhet på 80% som anses vara bra och implementerbar hos världens företag. Implementeringen av Foresight Triangulation på fallstudien hos WSP resulterade i en zombielista som angav två övergripande sektorer (Transport & Infrastructure samt Industry) med underliggande undersektorer som troligtvis kommer att ersättas år 2026.
The study shows that a triangulation method for performing foresight can be applied in a resource efficient way. The developed method Foresight Triangulation produced an accuracy of 80% which is considered good and implementable at the world's enterprises. The implementation of Foresight Triangulation on the case study at WSP resulted in a zombie list that indicated two overall sectors (Transport & Infrastructure and Industry) with underlying subsectors that are likely to be replaced by 2026.

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Weston, Alan Edward. "Building and using operational tools associated with time of travel forecasting of pollution in rivers, and behaviour analysis of water resource supply systems." Thesis, Lancaster University, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.423555.

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Hunt, Julian David. "Integration of rationale management with multi-criteria decision analysis, probabilistic forecasting and semantics : application to the UK energy sector." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:2cc24d23-3e93-42e0-bb7a-6e39a65d7425.

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This thesis presents a new integrated tool and decision support framework to approach complex problems resulting from the interaction of many multi-criteria issues. The framework is embedded in an integrated tool called OUTDO (Oxford University Tool for Decision Organisation). OUTDO integrates Multi-Criteria Decision Analysis (MCDA), decision rationale management with a modified Issue-Based Information Systems (IBIS) representation, and probabilistic forecasting to effectively capture the essential reasons why decisions are made and to dynamically re-use the rationale. In doing so, it allows exploration of how changes in external parameters affect complicated and uncertain decision making processes in the present and in the future. Once the decision maker constructs his or her own decision process, OUTDO checks if the decision process is consistent and coherent and looks for possible ways to improve it using three new semantic-based decision support approaches. For this reason, two ontologies (the Decision Ontology and the Energy Ontology) were integrated into OUTDO to provide it with these semantic capabilities. The Decision Ontology keeps a record of the decision rationale extracted from OUTDO and the Energy Ontology describes the energy generation domain, focusing on the water requirement in thermoelectric power plants. A case study, with the objective of recommending electricity generation and steam condensation technologies for ten different regions in the UK, is used to verify OUTDO’s features and reach conclusions about the overall work.

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Бабій, І. А. "Активізація економічного зростання на регіональному рівні (на прикладі Одеської області)." Thesis, Одеський національний економічний університет, 2021. http://local.lib/diploma/Babii3.pdf.

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Доступ до роботи тільки на території бібліотеки ОНЕУ, для переходу натисніть на посилання нижче
У роботі розглядаються теоретичні аспекти економічного розвитку, фактори його забезпечення, індикатори та державне стимулювання економічного зростання на регіональному рівні. Проаналізовано основні складові економічного потенціальну Одеської області Запропоновано пріоритетні напрямки для активізації економічного зростання в Одеській області.
The theoretical aspects of economic development, factors of its provision, indicators and state stimulation of economic growth at the regional level are considered in the work. The main components of the economic potential of Odessa region are analyzed Priority directions for intensification of economic growth in Odessa region are offered.

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Міх, О. М. "Формування трансформаційної системи забезпечення розвитку шкіряно-взуттєвої промисловості України." Thesis, Чернігів, 2017. http://ir.stu.cn.ua/123456789/15534.

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Міх, О. М. Формування трансформаційної системи забезпечення розвитку шкіряно-взуттєвої промисловості України : дис. ... канд. екон. наук : 08.00.03 / О. М. Міх. - Чернігів, 2017. - 293 с.
Дисертаційна робота присвячена поглибленню теоретико-методичних положень та розробка практичних рекомендацій щодо формування трансформаційної системи забезпечення розвитку шкіряно-взуттєвої промисловості України. У роботі представлено вдосконалений методичний підхід до формування механізму забезпечення розвитку шкіряно-взуттєвої промисловості України та запропоновано інструментарій оцінки необхідності впровадження трансформацій у шкіряно-взуттєвій промисловості України. Обґрунтовано алгоритм впровадження системи управління трансформаційними процесами в контексті забезпечення розвитку шкіряно-взуттєвої промисловості України. Запропоновано класифікацію видів трансформацій відповідно до чинників впливу на трансформаційний процес, яка може розглядатися на: рівні економіки країни, на рівні промисловості та на рівні суб’єктів господарювання, що дозволяє виділити особливості трансформаційних процесів за ієрархією. Розроблено наукові положення щодо формування трансформаційного процесу забезпечення розвитку економіки країни як системи, які включають впорядковану сукупність напрямів, принципів, методів, інструментів і засобів, та інших складових трансформаційної системи економіки з урахуванням економічної, фінансової, екологічні, інноваційної, соціальної складових та складової державного регулювання.
Диссертация посвящена углублению теоретико-методических положений и разработке практических рекомендаций по формированию трансформационной системы обеспечения развития кожевенно-обувной промышленности Украины. В работе представлен методический подход к формированию механизма обеспечения развития кожевенно-обувной промышленности Украины, который позволяет определить необходимость внедрения трансформаций на разных уровнях экономической системы, разработать направления по их внедрению и оценить эффективность формирования трансформационных процессов в прогнозном периоде. Предложено инструментарий оценки необходимости внедрения трансформаций в кожевенно-обувной промышленности Украины, который предусматривает: определение интегральных показателей по каждой подсистеме предприятия, установление сводного показателя необходимости и целесообразности внедрения трансформаций, разработку многофакторных моделей на основе корреляционно-регрессионного анализа, которые дают возможность получить генетический и целевой прогнозы, оптимизировать интегральные показатели и определить этап жизненного цикла в контексте внедрения трансформационных процессов. Обоснованно алгоритм внедрения системы управления трансформационными процессами, который предусматривает: оценку четырех групп факторов, синтезирования рассчитанных интегральных показателей и определение их прогнозных значений с последующим сравнением и интерпретацией результатов. Предложена классификация видов трансформаций в соответствии с факторами влияния на трансформационный процесс, который может рассматриваться на: уровне экономики страны, промышленности и субъектов хозяйствования. Разработаны научные положения по формированию трансформационного процесса обеспечения развития экономики страны, как системы, включающей упорядоченную совокупность направлений, принципов, методов, инструментов и средств, и других составляющих трансформационной системы экономики с учетом экономической, финансовой, экологической, инновационной, социальной составляющих и составляющей государственного регулирования.
The dissertation is devoted to the deepening of theoretical and methodological positions and the development of practical recommendations for the formation of a transformational system for providing the development of the leather and footwear industry in Ukraine. The paper suggests an improved methodical approach to the formation of a mechanism for the development of the leather and footwear industry in Ukraine and offers an instrument for assessing the need for the implementation of transformations in the leather and footwear industry of Ukraine. The algorithm of the control system implementation for the transformation processes in the context of ensuring the development of the leather and footwear industry in Ukraine is substantiated. The classification of types of transformations according to the factors of influence on the transformation process, which can be considered at the level of economy of the country, the level of industry and the level of subjects of management, allows to highlight the peculiarities of transformational processes in the hierarchy. The scientific positions concerning the formation of the transformational process of ensuring the development of the country's economy as a system that includes an ordered set of directions, principles, methods, tools and tools and other components of the transformational system of the economy taking into account economic, financial, environmental, innovation, social components and the components of state regulation are developed.

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Александрова, Вікторія Олександрівна. "Формування економіко-організаційного забезпечення реорганізації діяльності промислового підприємства." Thesis, Національний технічний університет "Харківський політехнічний інститут", 2020. http://repository.kpi.kharkov.ua/handle/KhPI-Press/48645.

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Дисертація на здобуття наукового ступеня кандидата економічних наук за спеціальністю 08.00.04 – економіка та управління підприємствами (за видами економічної діяльності). – Національний технічний університет "Харківський політехнічний інститут". – Харків, 2020. Обґрунтовано сутність дефініції "реорганізація діяльності промислового підприємства". Розроблено теоретико-методичні положення формування організаційно-економічного забезпечення реорганізації діяльності промислових підприємств, що містять: виділення функціональних складових наскрізних бізнес-процесів; формування функціональних зон і організаційних контурів; виокремлення цілей, форм й видів реорганізації діяльності. Проаналізовано фінансовий стан та економічну діяльність суб‘єктів господарювання машинобудівного комплексу України. Сформовано науково-практичні рекомендації щодо визначення факторів впливу на ефективність діяльності промислових підприємств, які передбачають оцінку генерації економічної доданої вартості та імітаційне моделювання закономірностей і взаємозв‘язків показників функціонування та розвитку підприємства. Удосконалено науково-методичний підхід до оцінювання рівнів економічного розвитку та активності, який базується на побудові моделей факторів, які характеризують функціональні зони і організаційні контури реорганізації діяльності промислового підприємства. Розроблено підходи до формування організаційно-економічного забезпечення реорганізації діяльності та прогнозування результатів запровадження важелів реорганізації діяльності промислового підприємства.
The dissertation on achieving a scientific degree of the candidate of economic sciences on a specialty 08.00.04 - economics and management of the enterprises (on kinds of economic activity). - National Technical University "Kharkiv Polytechnic Institute", Kharkiv, 2020. The dissertation is devoted to the development and scientific substantiation of theoretical and scientific-methodical approaches to the development of organizational and economic support for the reorganization of industrial enterprises. The world tendencies of development of mechanical engineering in the world and in the national economy, the basic theoretical approaches concerning the formation of organizational and economic maintenance of carrying out of the reorganization of the industrial enterprise are investigated. Justified the definition of «reorganization of an industrial enterprise» is substantiated, which takes into account the key competencies of the functioning and development of the socio-economic system with the separation of end-to-end business processes to ensure the generation of added economic value. Justified necessity to take into account the functional components (marketing, design, production preparation, procurement and logistics, quality monitoring, product sales, support, and maintenance) of the end-to-end business process, which reflects the implementation of key competencies of the business entity, structural elements (management, main, auxiliary), the formation of functional areas and organizational circuits. The main forms and types of the reorganization of an industrial enterprise are singled out in coordinates: technology, space, time, structure, clients, result, which is the basis for developing methodological approaches to assessment, diagnosis of its financial and economic condition, and formation of reorganization measures. Theoretical and methodological provisions for the formation of organizational and economic support for the reorganization of industrial enterprises, containing: the allocation of functional components of end-to-end business processes; formation of functional zones and organizational contours; identification of goals, forms, and types of the reorganization of activities. The financial condition and economic activity of economic entities of the machine-building complex of Ukraine are analyzed. Scientific and practical recommendations for determining the factors influencing the efficiency of industrial enterprises, which include the assessment of the generation of economic value-added and simulation of patterns and relationships of indicators of operation and development of the enterprise. An improved scientific and methodological approach to assessing the levels of economic development and activity, which is based on the construction of models of factors that characterize the functional areas and organizational contours of the reorganization of the industrial enterprise. The formation of organizational and economic support for the reorganization of the industrial enterprise is based on economic and mathematical modeling and game theory in determining the sets of targeted measures of reorganization by areas and takes into account the relationship and interdependence of their impact on internal and external factors of efficiency. combinations of financial, economic, and organizational tools for the reorganization of the industrial enterprise with certain parameters of influence. The approach to the formation of organizational and economic maintenance of reorganization of activity and forecasting of results of the introduction of levers of the reorganization of activity of the industrial enterprise based on the scenario approach, taking into account restrictions of financial and economic character and definition of the period of achievement of the target level of generation of economic added value is developed. application and implementation in the medium term. The developed proposals are brought to the level of methodical approaches, and their practical implementation in the context of the development of organizational and economic support of the reorganization of industrial enterprises of the Kharkiv region proved their practical significance and expediency of further use of the formed tools.

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Александрова, Вікторія Олександрівна. "Формування економіко-організаційного забезпечення реорганізації діяльності промислового підприємства." Thesis, Національний технічний університет "Харківський політехнічний інститут", 2020. http://repository.kpi.kharkov.ua/handle/KhPI-Press/49122.

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Дисертація на здобуття наукового ступеня кандидата економічних наук за спеціальністю 08.00.04 – економіка та управління підприємствами (за видами економічної діяльності). – Національний технічний університет «Харківський політехнічний інститут», Харків, 2020. Дисертацію присвячено розробці та науковому обґрунтуванню теоретичних і науково-методичних підходів щодо розвитку організаційно-економічного забезпечення реорганізації промислових підприємств. Досліджено світові тенденції розвитку машинобудування в світі та в національній економіці, основні теоретичні підходи щодо формування організаційно-економічного забезпечення проведення реорганізації промислового підприємства. Обґрунтовано сутність дефініції «реорганізація діяльності промислового підприємства», яке враховує ключові компетенції функціонування та розвитку соціально-економічної системи з виокремленням наскрізних бізнес-процесів для забезпечення генерації доданої економічної вартості. Обґрунтовано необхідність при реорганізації діяльності промислового підприємства враховувати функціональні складові (маркетинг, проектування, підготовка виробництва, закупівлі та логістика, моніторинг якості, реалізація продукції, підтримка та супроводження) наскрізного бізнес-процесу, що відображає реалізацію ключових компетенцій суб‘єкта господарювання, структурних елементів (управлінських, основних, допоміжних), формування функціональних зон і організаційних контурів. Виокремлено основні форми й види проведення реорганізації промислового підприємства в координатах: технологія, простір, час, структура, клієнти, результат, що є у підґрунтям розробки методичних підходів до оцінки, діагностики його фінансово-економічного стану та формуванні заходів проведення реорганізації. Розроблено теоретико-методичні положення формування організаційно-економічного забезпечення реорганізації діяльності промислових підприємств, що містять: виділення функціональних складових наскрізних бізнес-процесів; формування функціональних зон і організаційних контурів; виокремлення цілей, форм й видів реорганізації діяльності. Проаналізовано фінансовий стан та економічну діяльність суб‘єктів господарювання машинобудівного комплексу України. Сформовано науково-практичні рекомендації щодо визначення факторів впливу на ефективність діяльності промислових підприємств, які передбачають оцінку генерації економічної доданої вартості та імітаційне моделювання закономірностей і взаємозв‘язків показників функціонування та розвитку підприємства. Удосконалено науково-методичний підхід до оцінювання рівнів економічного розвитку та активності, який базується на побудові моделей факторів, які характеризують функціональні зони і організаційні контури реорганізації діяльності промислового підприємства Формування організаційно-економічного забезпечення реорганізації діяльності промислового підприємства базується на економіко-математичному моделюванні та теорії ігор при визначенні комплексів цільових заходів реорганізації за напрямами та враховує взаємозв‘язок та взаємообумовленість їх впливу на внутрішні та зовнішні фактори формування рівня досягнення ефективності, що дозволяє визначати найбільш доцільні комбінації фінансово-економічного і організаційного інструментарію реорганізації діяльності промислового підприємства з визначеними параметрами впливу. Розроблено підхід до формування організаційно-економічного забезпечення реорганізації діяльності та прогнозування результатів запровадження важелів реорганізації діяльності промислового підприємства,що ґрунтується на сценарному підході, врахуванні обмежень фінансово-економічного характеру та визначенні періоду досягнення цільового рівня генерації економічної доданої вартості, що дозволяє підвищити ступінь обґрунтованості доцільності їх застосування та реалізації у середньостроковій перспективі. Розроблені пропозиції доведені до рівня методичних підходів, а їх практична реалізація у контексті розвитку організаційно-економічного забезпечення реорганізації промислових підприємств Харківського регіону довела їх практичну значущість і доцільність подальшого використання сформованого інструментарію.
The dissertation on achieving a scientific degree of the candidate of economic sciences on a specialty 08.00.04 - economics and management of the enterprises (on kinds of economic activity). – National Technical University «Kharkiv Polytechnic Institute», Kharkiv, 2020. The dissertation is devoted to the development and scientific substantiation of theoretical and scientific-methodical approaches to the development of organizational and economic support for the reorganization of industrial enterprises. The world tendencies of development of mechanical engineering in the world and in the national economy, the basic theoretical approaches concerning the formation of organizational and economic maintenance of carrying out of the reorganization of the industrial enterprise are investigated. Justified the definition of «reorganization of an industrial enterprise» is substantiated, which takes into account the key competencies of the functioning and development of the socio-economic system with the separation of end-to-end business processes to ensure the generation of added economic value. Justified necessity to take into account the functional components (marketing, design, production preparation, procurement and logistics, quality monitoring, product sales, support, and maintenance) of the end-to-end business process, which reflects the implementation of key competencies of the business entity, structural elements (management, main, auxiliary), the formation of functional areas and organizational circuits. The main forms and types of the reorganization of an industrial enterprise are singled out in coordinates: technology, space, time, structure, clients, result, which is the basis for developing methodological approaches to assessment, diagnosis of its financial and economic condition, and formation of reorganization measures. Theoretical and methodological provisions for the formation of organizational and economic support for the reorganization of industrial enterprises, containing: the allocation of functional components of end-to-end business processes; formation of functional zones and organizational contours; identification of goals, forms, and types of the reorganization of activities. The financial condition and economic activity of economic entities of the machine-building complex of Ukraine are analyzed. Scientific and practical recommendations for determining the factors influencing the efficiency of industrial enterprises, which include the assessment of the generation of economic value-added and simulation of patterns and relationships of indicators of operation and development of the enterprise. An improved scientific and methodological approach to assessing the levels of economic development and activity, which is based on the construction of models of factors that characterize the functional areas and organizational contours of the reorganization of the industrial enterprise The formation of organizational and economic support for the reorganization of the industrial enterprise is based on economic and mathematical modeling and game theory in determining the sets of targeted measures of reorganization by areas and takes into account the relationship and interdependence of their impact on internal and external factors of efficiency. combinations of financial, economic, and organizational tools for the reorganization of the industrial enterprise with certain parameters of influence. The approach to the formation of organizational and economic maintenance of reorganization of activity and forecasting of results of the introduction of levers of the reorganization of activity of the industrial enterprise based on the scenario approach, taking into account restrictions of financial and economic character and definition of the period of achievement of the target level of generation of economic added value is developed. application and implementation in the medium term. The developed proposals are brought to the level of methodical approaches, and their practical implementation in the context of the development of organizational and economic support of the reorganization of industrial enterprises of the Kharkiv region proved their practical significance and expediency of further use of the formed tools.

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46

Barth, Joseph. "UPS-SCS weekly forecasting tool." 2009. http://etd.louisville.edu/data/UofL0473t2009.pdf.

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Thesis (M.Eng.)--University of Louisville, 2009.
Title and description from thesis home page (viewed May 15, 2009). Department of Industrial Engineering. Vita. "May 2009." Includes bibliographical references (p. 37).

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47

Liao, Chung-Jen, and 廖崇仁. "Using Back-Propagation Network for Building Machine Tool Forecasting System." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/81776351646380805223.

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碩士
朝陽科技大學
資訊管理系碩士班
99
As the IT technology improves rapidly, competition between enterprises gets more complicated and intensified. Due to the lack of resources, small-and-medium-sized enterprise (SME) must react promptly and to cope with the various request from the customer. How to shorten the production life cycle and how to minimize the cost has become very critical issues for SMEs. It is therefore the SMEs need to reduce the reaction time and to perform the accurate cost estimation. 　　The business of Computer Numerical Control (CNC) is one of these types of typical companies in Taiwan that fights for quick response time. To derive an accurate quotation for the customer, 3 major skills are needed for quick responding and for cost estimation. These three skills are setting up of machining parameters, programming, and operation of machine. With programming, a CNC technician must familiar with CAD/CAM software, transferring the drawing into CNC program (also called G-Code), and feeding to CNC machine [20]. The traditional way of deriving a quotation relies on the experienced technician(s) which will usually spend many days for figuring out the possible cost. However, this way of quotation estimation is time consuming and, hence, is costly. Therefore, this research intends to construct an automated way for choosing the proper CNC machine in short time and, therefore, to reduce the cost that was resulted from the manual processing of traditional way. 　　It is known that Artificial Neural Network (ANN) is useful to solve the unstructured problem [Zhong-Ping Wang(1997)]. This research employs the ANN to learn the knowledge of selecting proper CNC machine. To achieve this goal, a Machine-Tool Forecasting System (MTFS) is proposed to solve the aforementioned problem. In order to allow the MTFS act like an expert, the proposed MTFS is trained to understand the parameters that fit to various CNC machine. The experiment of this research uses 8 difference CNC machine for testing. The result shows very promising outcome, i.e., the MTFS is able to choose a proper machine tool within very short time and, therefore, can reduce the processing time for better quotation.

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Huang, Chen-Wei, and 黃呈瑋. "Patent Life Cycle as A Technological Forecasting Tool for Biped Walking Robot in Janpanese." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/84192490043162043870.

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碩士
華梵大學
工業工程與經營資訊學系碩士班
96
ABSTRACT The patent is a ring which compatriots and enterprise-like corporation pay attention to most at present. Among them forgive a lot of important technical informations. It is the important indicators of science and technology and economic development in the future.This text searches the patent database of licensing drawing room in Japan. Technology of Biped Walking Robot、The growth forecasting which carries on the patent piece.First of all、three every way is it predict patent to develop present situation future to used for by way of Pearl model、Gompertz model、Logistic model,etc.. S-curve model implements the linearization Analyse and regression analysis ,Find out the parameter of every model ,Calculate out point of inflection 、growth time 、saturation time、practice error . Predict by Loglet Lab software system and Microsoft Excel software is it is it calculate to forecasting to run on、Make several possible saturation values. And the forecasting and analysis that carried on every model. And、discuss the analysis of One-way ANOVA absolute error sum. According to the result of this research、Gompertz model and obvious error of actual value are less and less、It will be greater and greater with the actual value error to review Logistic and Pearl model. According to the forecasting of Gompertz model、Field of technology about the fact that Biped Walking Robot. Because just entered growth stage、And there is very large space that can grow up、It is estimated that will not be close to the saturation point until 2077. The patent piece of this field will grow up continuously、Forecasting end time for growth is about A.D. 2079~2082. The patent information is applied to technological forecasting、Is it define the feasible concrete illustration very much to propose.

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Shan, Zhi-Heng, and 單志恆. "Application of Deep Neural Network for Forecasting Taiwan\'\'s Machine Tool Exports to China." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/3krsbv.

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碩士
國立中興大學
企業管理學系所
107
Machine tool industry plays a vital role in Taiwan''s economic development. The machine tool exports affect gross domestic product (GDP) in Taiwan significantly. The leading importer for Taiwan''s machine tools is China, many countries apply themselves to export machine tools to China and so is Taiwan. The machine tool exports to China in some countries are highly overlapping with Taiwan. In a highly competitive enviroment, effective forecasting models help machine tool manufacturers improve their predictive effectiveness and business competitiveness. This research utilizes two sampling approaches to build the predictive models, including random sampling and non-random sampling schemes. In random sampling, an arbitrary value is set as the seed for the random numbers, and then the observations are divided as training set and testing set stochastically. The parameters for deep neural network, back-propagation neural network, and support vector machine are determined based on the first training set and testing set. Then 400 replications are performed as the simulation experiments to calculate the performance measures MAPE, MAE, and MSE. In non-random sampling approach, the observations from 2002 to 2016 are collected as training set, and the latest observations in 2017 are selected as testing set. The predicting models considered here are time series model, SARIMA, deep neural network, back-propagation neural network, and support vector machine. The results show that the performance of deep neural network is better than back-propagation neural network and support vector machine in random sampling. In non-random sampling, the performance of deep neural network is also superior to back-propagation neural network and support vector machine.

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Cheng-Chang, Chang, and 張正昌. "The Study on Establishing Technological Forecasting Model using of Patent Information -A Case Study of power hand tool." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/10467625024230298242.

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碩士
中華大學
科技管理研究所
93
Market demand is the pulling force that enterprises manage. The development in science and technology is to accelerate the thrust that the industry upgrades fast. The application of a lot of new science and technology is enough to train the new industry, Change the type of operation of enterprises. Carrying on technological prediction can help the manager to plan the technological developing direction and assign the input and guide which research and develop resources to R&D the achievement output. In the past several years, the export value of the hand tool was continued to hold the first in several main industrial countries in the world. But, China is devoted to promoting the development of industry in recent years. China will have already become the global largest export country of hand tool in 2003. So industry upgrading is the outlet of production and sales in the future of hand tool industry under the drive that the Taiwan hand tool industry makes the transition in the structure. So this research regards power hand tool as the analysis target. At first review the analytical method of the patent. Utilize Delphion-IPN to collect the relevant patent information of power hand tool. And the Unite States, Europe and Japan for the main economy in the world, so regard the patents of this three major economies as the main analysis target. Secondly prove that the industry develops the background and present situation. Third, put in order and analysis the patent materials, utilize Loglet Lab software to analysis that growth curves, Power hand tool industry is during maturity stage. Set up the way of predicting by Pearl Curve, Gompertz Curve and Grey model. The result is relatively good with the prediction result of Grey model.

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Dissertations / Theses on the topic 'FORECASTING TOOL'

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