Tesis sobre el tema "Forecasting – Research"
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Bruno, Jack H. "Evaluating the Weather Research and Forecasting Model Fidelity for Forecasting Lake Breezes". Ohio University Honors Tutorial College / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ouhonors1556189524538244.
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Nissan, Hannah. "Modelling rainfall erosivity using the Weather Research and Forecasting model". Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/24681.
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Soil erosion is a serious threat to agricultural productivity and the sustainable provision of food to a growing world population. Current erosion models employ simplistic treatments of rainfall. This thesis presents a new approach to erosion modelling, using the Weather Research and Forecasting model to simulate rainfall erosivity, an indicator of the erosive capacity of rain. Rainfall erosivity is modelled in the Caucasus region, an area vulnerable to erosion and climate change pressures. Low intensity rainfall (below 2 mmhr^{-1}) is found to contribute significantly to erosivity (23%), contrary to common assumptions. An exponential dependence of the fraction of erosivity from light rain on the proportion of light rain is found. Erosion models focus on storms, but results suggest that storm-based calculations may exclude up to 30% of erosivity. In the Universal Soil Loss Equation, this does not lead to errors in long term soil loss but could cause an underestimation of event erosion. Rainfall kinetic energy flux is an important variable in erosion prediction and is routinely parameterised from intensity. Here this is dynamically simulated from basic physics in a cloud resolving model, using four microphysics schemes. Results are within the range of observations and capture the observed variability in kinetic energy for a given intensity, where current methods fail. Large raindrops are shown to contribute disproportionately to total kinetic energy, and also to surface precipitation, compared with their number. No connection has hitherto been drawn between aerosols and soil erosion. The effect of aerosols on rainfall erosivity is investigated in a cloud resolving model. Aerosols can either enhance or suppress precipitation. In both these cases the response of erosivity to a rise in aerosols is in the same direction as, but amplified beyond, the change in total rain. It is also shown that aerosols can influence erosivity by changing raindrop sizes. These results suggest that anthropogenic aerosol emissions affect erosivity and thus may have important consequences for agricultural productivity.
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McCarty, Laura Smith. "Evaluation and recommendation of storage space forecasting model(s)". Thesis, Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/24250.
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Mehalic, Charles J. "Multiparameter forecasting techniques for the Marine Corps officer rate generator". Thesis, Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA241453.
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Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 1990.Thesis Advisor(s): Read, Robert R. Second Reader: Whitaker, Lyn R. "September 1990." Description based on title screen as viewed on March 19, 2010. DTIC Identifier(s): Forecast, Seasonality, Attrition Estimation, Harrison, Winters, Bayesian, Expotential Smoothing, Shrinkage, Aggregation. Author(s) subject terms: Forecast, Attrition Estimation, Harrison, Winters, Bayesian, Seasonality, Expotential smoothing, Shrinkage, Aggregation. Includes bibliographical references (p. 100-101). Also available in print.
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Hong, Tao. "Long-Term Spatial Load Forecasting Using Human-Machine Co-construct Intelligence Framework". NCSU, 2008. http://www.lib.ncsu.edu/theses/available/etd-10212008-105450/.
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This thesis presents a formal study of the long-term spatial load forecasting problem: given small area based electric load history of the service territory, current and future land use information, return forecast load of the next 20 years. A hierarchical S-curve trending method is developed to conduct the basic forecast. Due to uncertainties of the electric load data, the results from the computerized program may conflict with the nature of the load growth. Sometimes, the computerized program is not aware of the local development because the land use data lacks such information. A human-machine co-construct intelligence framework is proposed to improve the robustness and reasonability of the purely computerized load forecasting program. The proposed algorithm has been implemented and applied to several utility companies to forecast the long-term electric load growth in the service territory and to get satisfying results.
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Inman, Oliver Lane. "Technology Forecasting Using Data Envelopment Analysis". PDXScholar, 2004. https://pdxscholar.library.pdx.edu/open_access_etds/2682.
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The ability to anticipate future capabilities of technology products has broad implications for organizations. Technological forecasting allows management to improve resource allocation, make better staffing decisions, and more confidently plan facilities and capital expenditures. Technology forecasting may also identify potential new markets and opportunities, such as finding ways to exploit current technology beyond its originally intended purposes.
Modern technology forecasters use an array of forecasting methods to predict the future performance of a technology, such as time-series analysis, regression, stochastic methods, and simulation. These quantitative methods rely on the assumption that past behavior will continue. Shortcomings include their lack of emphasis on the best technology available and the fact that they do not effectively address the dynamic nature of ever changing trade-off surfaces. This research proposes a new method to address the shortcomings of common forecasting techniques by extending a well-established management science methodology known as data envelopment analysis (DEA). This new method is referred to as Technology Forecasting with Data Envelopment Analysis (TFDEA). Three case studies are examined to determine the method's validity.
The first case study is that of relational database system performance based upon industry benchmarks obtained from the Transaction Processing Performance Council (TPC). The results reveal that TFDEA provides a more accurate picture of the state of the art than basic regression. The second case study expands Moore's law to six dimensions, resulting in a more comprehensive assessment of microprocessor technology. The final case study re-examines hard disk drive data for the years 1994-1999 in order to evaluate the technological progress of multiple technological approaches presented in Christensen's The Innovator's Dilemma .
Major contributions include both a new technology forecasting technique and an important extension of the temporal DEA methodology, which together offer a new and more comprehensive method for evaluating and forecasting technology.
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Freixieiro, Gomes de Mello Rafael. "Design-led future forecasting model for mobile communications". Thesis, Brunel University, 2016. http://bura.brunel.ac.uk/handle/2438/13142.
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Since the establishment of the wireless sector, design has been playing a wide range of roles. Specialized literature has been extensively reporting the use of this discipline associated with NPD, focusing on hardware and software development in the mobile communications. On the other hand, evidences of its use to support forecasting are scarce and generic. Finally, formal publications addressing future forecasting from a design perspective in the context of mobile communications have never been reported, leading to a knowledge gap that needs to be addressed. This research investigates the strategic roles, applications and contributions of design and designers for future forecasting in the wireless telecom sector. As a comprehensive discipline, it is used to examine and identify a number of factors that might influence/impact in the development of visionary solutions supporting the design team of traditional handset manufacturers to make better decisions in order to ‘shape’ the future in the wireless industry. Considering these ideas, the aim of this research is to create a ‘design-led future forecasting model for mobile communications’ to assist and support traditional manufacturers’ design team. This PhD study relies on a qualitative methodology comprising a number of data collection and analysis tools (e.g. literature review, case studies analysis, in-depth experts’ interviews, workshops and Grounded Theory). To create the intended framework, extensive secondary and primary data; theoretical and practical inputs were brought together, analysed and combined. The proposed model was evaluated through two rounds of experts’ interviews complemented by two workshops with potential users (e.g. design students) to check and explore its practicalities when applied to design for the future. Finally, this study bridges future forecasting and the wireless telecom through the use of design to address the literature gap. The richness of the developed model provides practical assistance to traditional manufacturer’s design team informing about a broad spectrum of aspects that should be considered when designing for the future in the mobile telecom industry, supporting strategic decision making in different stages of the future-led design process.
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Calmon, André du Pin. "Reverse logistics for consumer electronics : forecasting failures, managing inventory, and matching warranties". Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/98720.
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Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2015.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 147-150).
The goal of this thesis is to describe, model, and optimize reverse logistics systems commonly used in the Consumer Electronics industry. The context and motivation for this work stem from a collaboration with an industrial partner, a Fortune 500 company that sells consumer electronics and is one of the top retailers in its sector. The thesis is divided into three parts. In the first part of the thesis we model and analyze the problem of forecasting failures of new products. When a new device is introduced to the market there is limited information available about its failure time distribution since most devices have yet to fail. However, there is extensive failure time data for prior devices, as well as evidence that the failure time distribution for new devices can be forecast from the data for prior devices. In this setting, we propose two strategies for forecasting the failure distribution of new products that leverages the censored failure observations for the new devices as well as this massive amount of data collected for prior devices. We validate these strategies using data from our industrial partner and using data from a social enterprise located in the Boston area. The second part of the thesis concerns inventory management in a reverse logistics system that supports the warranty returns and replacement for a consumer electronic device. This system is a closed-loop supply chain since failed devices are refurbished and are kept in inventory to be used as replacement devices or are sold through a side-sales channel. Furthermore, managing inventory in this system is challenging due to the short life-cycle of this type of device and the rapidly declining value for the inventory that could potentially be sold. We propose a stochastic model that captures the dynamics of inventory of this system, including the limited life-cycle and the declining value of inventory that can be sold off. We characterize the structure of the optimal policy for this problem. In addition, we introduce two heuristics: (i) a certainty-equivalent approximation, which leads to a simple closed form policy; and (ii) a dual balancing heuristic, which results in a more tractable newsvendor type model. We also develop a robust version of this model in order to obtain bounds for the overall performance of the system. The performance of these heuristics is analyzed using data from our industrial partner. The final part of the thesis concerns the problem faced by a consumer electronics retailer when matching devices in inventory to customers. More specifically, we analyze a setting where there are two warranties in place: (i) the consumer warranty, offered by the retailer to the consumer, and (ii) the Original Equipment Manufacturer (OEM) warranty, offered by the OEM to the retailer. Both warranties are valid for a limited period (usually 12 months), and once warranties expire, the coverage to replace or repair a faulty device ends. Thus, a customer does not receive a replacement if he/she is out of consumer warranty, and the retailer cannot send the device to the OEM for repairs if it is out of OEM warranty. The retailer would ideally like to have the two warranties for a device being matched, i.e., the customer would have the same time left in his consumer warranty as the device would have left in the OEM warranty. A mismatch between these warranties can incur costs to the retailer beyond the usual processing costs of warranty requests. Namely, since a device can fail multiple times during its lifecycle the replacement device sent to customers that file warranty requests can lead to out-of-OEM-warranty returns. In order to mitigate the number of out-of-OEM-warranty returns, we propose an online algorithm to match customers that have filed warranty claims to refurbished devices in inventory. The algorithm matches the oldest devices in inventory to the oldest customers in each period. We characterize the competitive ratio of this algorithm and, through numerical experiments using historical data, demonstrate that it can significantly reduce out of warranty returns compared to our partner's current strategy.
by Andre du Pin Calmon.
Ph. D.
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Chan, San-wing Frederick. "Developing inquiry based learning in secondary geography education topic weather forecast : an action research /". Click to view the E-thesis via HKUTO, 2003. http://sunzi.lib.hku.hk/hkuto/record/B3984870X.
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Conatser, Dean G. "Forecasting U.S. Marine Corps reenlistments by military occupational specialty and grade". Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Sep%5FConatser.pdf.
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Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 2006.Thesis Advisor(s): Ronald D. Fricker. "September 2006." Includes bibliographical references (p. 49-50). Also available in print.
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Boyer, Christopher A. (Christopher Andrew). "Statistical methods for forecasting and estimating passenger willingness-to-pay in airline revenue management". Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/61191.
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Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2010.Page 170 blank. Cataloged from PDF version of thesis.
Includes bibliographical references (p. 167-169).
The emergence of less restricted fare structures in the airline industry reduced the capability of airlines to segment demand through restrictions such as Saturday night minimum stay, advance purchase, non-refundability, and cancellation fees. As a result, new forecasting techniques such as Hybrid Forecasting and optimization methods such as Fare Adjustment were developed to account for passenger willingness-to- pay. This thesis explores statistical methods for estimating sell-up, or the likelihood of a passenger to purchase a higher fare class than they originally intended, based solely on historical booking data available in revenue management databases. Due to the inherent sparseness of sell-up data over the booking period, sell-up estimation is often difficult to perform on a per-market basis. On the other hand, estimating sell-up over an entire airline network creates estimates that are too broad and over-generalized. We apply the K-Means clustering algorithm to cluster markets with similar sell-up estimates in an attempt to address this problem, creating a middle ground between system-wide and per-market sell-up estimation. This thesis also formally introduces a new regression-based forecasting method known as Rational Choice. Rational Choice Forecasting creates passenger type categories based on potential willingness-to-pay levels and the lowest open fare class. Using this information, sell-up is accounted for within the passenger type categories, making Rational Choice Forecasting less complex than Hybrid Forecasting. This thesis uses the Passenger Origin-Destination Simulator to analyze the impact of these forecasting and sell-up methods in a controlled, competitive airline environment. The simulation results indicate that determining an appropriate level of market sell-up aggregation through clustering both increases revenue and generates sell-up estimates with a sufficient number of observations. In addition, the findings show that Hybrid Forecasting creates aggressive forecasts that result in more low fare class closures, leaving room for not only sell-up, but for recapture and spill-in passengers in higher fare classes. On the contrary, Rational Choice Forecasting, while simpler than Hybrid Forecasting with sell-up estimation, consistently generates lower revenues than Hybrid Forecasting (but still better than standard pick-up forecasting). To gain a better understanding of why different markets are grouped into different clusters, this thesis uses regression analysis to determine the relationship between a market's characteristics and its estimated sell-up rate. These results indicate that several market factors, in addition to the actual historical bookings, may predict to some degree passenger willingness-to-pay within a market. Consequently, this research illustrates the importance of passenger willingness-to-pay estimation and its relationship to forecasting in airline revenue management.
by Christopher A. Boyer.
S.M.
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Lou, Mei Meng. "Weather simulation in Macao using the Weather Research and Forecasting (WRF) Model". Thesis, University of Macau, 2009. http://umaclib3.umac.mo/record=b1943035.
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Damauskaitė, Jovita. "Research And Application Of Hard Cosmic Ray Flux For Forecasting Meteorological Conditions". Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2010. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2010~D_20101222_130615-72153.
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The thesis investigates cosmic rays and their scattering in the atmosphere and the change in their intensity caused by the frequency of meteorological phenomenon. The main objective of the research is the change in cosmic rays as well as atmospheric pressure and estimation of their connection. A thorough analysis and interpretation allow to supplement meteorological information for weather forecasts.Disertacijoje nagrinėjama kosminė spinduliuotė ir jos sklaida atmosferoje bei jos intensyvumo kaita, kurią lemią meteorologinių reiškinių dažnumas. Pagrindinis tyrimo objektas yra kietosios kosminės spinduliuotės ir atmosferos slėgio pokyčiai bei jų sąryšio įvertinimas. Kosminės spinduliuotės duomenų detali analizė ir interpretacija leidžia papildyti meteorologinę informaciją orų prognozei.
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Zhai, Yusheng. "Time series forecasting competition among three sophisticated paradigms /". Electronic version (Microsoft Word), 2005. http://dl.uncw.edu/etd/2005/zhaiy/yushengzhai.html.
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Montornès, Torrecillas Alex. "A study of the shortwave schemes in the Weather Research and Forecasting model". Doctoral thesis, Universitat de Barcelona, 2017. http://hdl.handle.net/10803/401501.
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The radiative transfer cannot be explicitly resolved in the atmospheric models for two reasons: i) a full treatment of the radiative transfer equation (RTE) requires a high amount of computational resources and ii) the radiative transfer fields such as the optical thickness are not a direct solution of the Euler equations and hence, they must be parameterized as a function of the meteorological fields. Consequently, the physical processes related with radiation are simplified and approximated in physical schemes.
In the particular case of the solar radiation, the use of these parameterizations were reduced for many years to represent the day/night cycle inside the model. Therefore, the accuracy of the solar schemes was left in the background and the computational resources were prioritized. With the growth of the solar energy industry during the last decade, a paradigm shift has occurred. Now, the solar irradiance (i.e. global horizontal GHI, direct horizontal DHI and diffuse DIF) becomes an important product for resource assessment as well as for forecasting applications.
The main objective of this thesis is the identification and quantification of the sources of error that have a direct or an indirect contribution to the accuracy of the solar schemes, particularly, in those available in the Weather Research and Forecasting (WRF-ARW) model, widely used in the sector.
First, the thesis presents a review of the set of physical approximations considered in six solar parameterizations available in the WRF-ARW model: Dudhia, Goddard, New Goddard, Rapid Radiative Transfer Model for General Circulation Models (RRTMG), Climate Atmospheric Model (CAM) and Fu-Liou-Gu (FLG).
The sources of error are limitations in the representation of the radiative transfer as a conse- quence of the set of approximations assumed by one scheme. In this thesis three sources of error are analyzed: i) errors due to the vertical discretization of the atmosphere in a set of layers that are assumed to be homogeneous (truncation error), ii) errors due to the misrepresentation of the layer between the top of the model (TOM) and the top of the atmosphere (TOA), called TOM error and iii) errors due to the physical simplifications and parameterizations in the RTE, named physical error.
In order to avoid the uncertainty introduced by the other components of the model, the source code of each one of the six solar schemes has been separated of the model and adapted for working with 1-dimensional vertical profiles.
The studies of the truncation and TOM errors are performed by using ideal vertical profiles under four scenarios: a dry atmosphere, a wet cloudless sky, low water cloud and a high ice cloud. The results for the ETOM show that for the typical range of TOM values in mesoscale appli- cations (i.e. 10 hPa), the error with respect to a full atmospheric column is less than 0.5% and
hence, the TOM error can be neglected.
The analysis of the Etrun reveals that the sensitivity of the solar schemes on the vertical config- uration (i.e. number of vertical levels and their distribution) is directly related with the method used for the vertical integration of the multiscattering processes. For the typical mesoscale config- urations, the Etrun under clear-sky conditions is determined around 1.1%, 0.9% and 4.9% for the GHI, DHI and DIF, respectively. In both cloudy scenarios, the Etrun increases significantly, being more important for the high clouds.
The Ephys is analyzed under clear-sky conditions using real soundings from the Integrated Global Radiosonde Archive data-set and comparing the irradiance outcomes with the Baseline Solar Radiation Network measurements. With the exception of Dudhia, the behavior for all the parameterizations is the same. A large overestimation of the DHI with a large underestimation of the DIF that leads to a near-zero bias for the GHI. Polar sites show the lowest errors with a mean MAE of 2.1%, 5.2% and 3.7% for GHI, DHI and DIF, respectively. Midlatitude sites show the worst results with a mean MAE of 3.4% in GHI, 11.6% in DHI and 7.8% in the DIF.L’objectiu principal d’aquesta tesi ´es la identificaci´o i quantificaci´o de les fonts d’error que tenen una contribuci´o directa o indirecta en la precisi´o dels esquemes solars, particularment en aquells disponibles en el model Weather Research and Forecasting (WRF-ARW), `ampliament emprat en el sector de l’energia solar. Les fonts d’error s´on limitacions en la representaci´o del transport radiatiu com a consequ¨`encia del conjunt d’aproximacions assumides per cada esquema. En aquesta tesi hi ha tres fonts d’error que s´on analitzades: i) l’error degut a la discretitzaci´o vertical de l’atmosfera en un conjunt d’estrats que s’assumeixen homogenis (error de truncament, Etrun), ii) l’error com a resultat d’una repre- sentaci´o insuficient de l’estrat entre el cim del model (TOM) i el cim de l’atmosfera (TOA), anomenat error de TOM Etom, i iii) l’error degut a les simplificacions i a les parametritzacions f´ısiques de l’RTE, definit com a error físic, Ephys. Per tal d’evitar la incertesa introdu¨ıda pels altres components del model, el codi font de cadas- cun dels sis esquemes solars ha estat separat del model i adaptat per treballar amb perfils verticals 1-dimensionals. Mitjan¸cant aquest m`etode, les habilitats dels esquemes solars poden ´esser anal- itzades sota condicions d’entrada id`entiques. D’una banda l’error de TOM i el de truncament s’analitzen a partir de perfils ideals. De l’altra, l’error f´ısic s’evalua prenent dades de radiosondatge com a perfil vertical i comparant les sortides dels esquemes radiatius amb mesures en superf´ıcie. Els resultats d’aquesta tesi mostren que l’Etom esdev´e negligible per la majoria d’aplicacions de mesoscala. Per configuracions t´ıpiques del model, l’Etrun en condicions de cel ser`e es troba al voltant de l’1.1%, el 0.9% i el 4.9% per la GHI, DHI i DIF, respectivament. En el cas amb nu´vols augmenta de forma significativa. L’estudi de l’Ephys mostra una relaci´o significativa amb el contingut de vapor d’aigua i els aerosols.
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Hou, Qingchuan. "Two essays on empirical accounting research /". View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?ACCT%202007%20HOU.
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See, Mei Eng Elaine. "How to detect the location and time of a covert chemical attack a Bayesian approach". Thesis, Monterey, California : Naval Postgraduate School, 2009. http://edocs.nps.edu/npspubs/scholarly/theses/2009/Dec/09Dec%5FSee.pdf.
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Thesis (M.S. in Operations Research)--Naval Postgraduate School, December 2009.Thesis Advisor: Kress, Moshe. Second Reader: Johnson, Rachel. "December 2009." Description based on title screen as viewed on February 1, 2010. Author(s) subject terms: Bayesian updating model, Atmospheric Threat and Dispersion model, estimation of location and time of a chemical attack, sensor placement. Includes bibliographical references (p. 99). Also available in print.
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Hartmann, Holly Chris. "Stakeholder driven research in a hydroclimatic context". Diss., FIND on the Web, 2001. http://hdl.handle.net/10150/191254.
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Tsang, Kwan-ming y 曾坤明. "Application of operation research techniques for forecasting transportation demand, planning train services and station facilitiesof the MTRC". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B42574717.
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Jones, Mark Benjamin. "A cost-benefit forecasting framework for assessment of advanced manufacturing technology development". Thesis, Cranfield University, 2014. http://dspace.lib.cranfield.ac.uk/handle/1826/9247.
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Development of new Advanced Manufacturing Technology (AMT) for the aerospace industry is critical to
enhance the manufacture and assembly of aerospace products. These novel AMTs require high development
cost, specialist resource capabilities, have long development periods, high technological risks and lengthy
payback durations. This forms an industry reluctance to fund the initial AMT development stages, impacting on
their success within an ever increasingly competitive environment.
Selection of suitable AMTs for development is typically performed by managers who make little reference to
estimating the non-recurring development effort in resources and hardware cost. In addition, the performance at
the conceptual stage is predicted using expert opinion, consisting of subjective and inaccurate outputs. AMTs
selected are then submerged into development research and heavily invested in, with incorrect selections having
a detrimental impact on the business.
A detailed study of the UK aerospace manufacturing industry corroborated these findings and revealed a
requirement for a new process map to resolve the problem of managing AMT developments at the conceptual
stages. This process map defined the final research protocol, forming the requirement for a Cost-Benefit
Forecasting Framework. The framework improves the decision making process to select the most suitable
AMTs for development, from concept to full scale demonstration. Cost is the first element and is capable of
estimating the AMT development effort in person-hours and cost of hardware using two parametric cost models.
Benefit is the second element and forecasts the AMT tangible and intangible performance. The framework plots
these quantified cost-benefit parameters and is capable of presenting development value advice for a diverse
range of AMTs with varied applications. A detailed case study is presented evaluating a total of 23 novel
aerospace AMTs verifying the capability and high accuracy of the framework within a large aerospace
manufacturing organisation. Further validation is provided by quantifying the responses from 10 AMT
development experts, after utilising the methodology within an industrial setting. The results show that
quantifying the cost-benefit parameters provides manufacturing research and technology with the ability to
select AMTs that provide the best value to a business.
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Pan, Xinwei. "FORECASTING THE WORKLOAD WITH A HYBRID MODEL TO REDUCE THE INEFFICIENCY COST". UKnowledge, 2017. http://uknowledge.uky.edu/me_etds/91.
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Time series forecasting and modeling are challenging problems during the past decades, because of its plenty of properties and underlying correlated relationships. As a result, researchers proposed a lot of models to deal with the time series. However, the proposed models such as Autoregressive integrated moving average (ARIMA) and artificial neural networks (ANNs) only describe part of the properties of time series. In this thesis, we introduce a new hybrid model integrated filter structure to improve the prediction accuracy. Case studies with real data from University of Kentucky HealthCare are carried out to examine the superiority of our model. Also, we applied our model to operating room (OR) to reduce the inefficiency cost. The experiment results indicate that our model always outperforms compared with other models in different conditions.
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Noble, Gregory Daniel. "Application of Modern Principles to Demand Forecasting for Electronics, Domestic Appliances and Accessories". Wright State University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=wright1245278595.
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Lim, Dong-Joon. "Technological Forecasting Based on Segmented Rate of Change". PDXScholar, 2015. https://pdxscholar.library.pdx.edu/open_access_etds/2220.
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Consider the following questions in the early stage of new product development. What should be the target market for proposed design concepts? Who will be the competitors and how fast are they moving forward in terms of performance improvements? Ultimately, is the current design concept and targeted launch date feasible and competitive?
To answer these questions, there is a need to integrate the product benchmarking with the assessment of performance improvement so that analysts can have a risk measure for their R&D target setting practices. Consequently, this study presents how time series benchmarking analysis can be used to assist scheduling new product releases. Specifically, the proposed model attempts to estimate the "auspicious" time by which proposed design concepts will be available as competitive products by taking into account the rate of performance improvement expected in a target segment.
The empirical illustration of commercial airplane development has shown that this new method provides valuable information such as dominating designs, distinct segments, and the potential rate of performance improvement, which can be utilized in the early stage of new product development. In particular, six dominant airplanes are identified with corresponding local RoCs and, inter alia, technological advancement toward long-range and wide-body airplanes represents very competitive segments of the market with rapid changes. The resulting individualized RoCs are able to estimate the arrivals of four different design concepts, which is consistent with what has happened since 2007 in commercial airplane industry.
In addition, the case study of the Exascale supercomputer development is presented to demonstrate the predictive use of the new method. The results indicate that the current development target of 2020 might entail technical risks considering the rate of change emphasizing power efficiency observed in the past. It is forecasted that either a Cray-built hybrid system using Intel processors or an IBM-built Blue Gene architecture system using PowerPC processors will likely achieve the goal between early 2021 and late 2022. This indicates that the challenge to improve the power efficiency by a factor of 23 would require the maximum delay of 4 years to reach the Exascale supercomputer compared to the existing performance curve.
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Smallman, Thomas Luke. "Atmospheric profiles of CO₂ as integrators of regional scale exchange". Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/8886.
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The global climate is changing due to the accumulation of greenhouse gases (GHGs) in the atmosphere, primarily due to anthropogenic activity. The dominant GHG is CO₂ which originates from combustion of fossil fuels, land use change and management. The terrestrial biosphere is a key driver of climate and biogeochemical cycles at regional and global scales. Furthermore, the response of the Earth system to future drivers of climate change will depend on feedbacks between biogeochemistry and climate. Therefore, understanding these processes requires a mechanistic approach in any model simulation framework. However ecosystem processes are complex and nonlinear and consequently models need to be validated against observations at multiple spatial scales. In this thesis the weather research and forecasting model (WRF) has been coupled to the mechanistic terrestrial ecosystem model soil-plant-atmosphere (SPA), creating WRF-SPA. The thesis is split into three main chapters: i. WRF-SPA model development and validation at multiple spatial scales, scaling from surface fluxes of CO₂ and energy to aircraft profiles and tall tower observations of atmospheric CO₂ concentrations. ii. Investigation of ecosystem contributions to observations of atmospheric CO₂ concentrations made at tall tower Angus, Dundee, Scotland using ecosystem specific CO₂ tracers at seasonal and interannual time scales. iii. An assessment of detectability of a policy relevant national scale afforestation by observations made at a tall tower. Detectability of changes in atmospheric CO₂ concentrations was assessed through a comparison of a control simulation, using current day forest extent, and an experimentally afforested simulation using WRF-SPA. WRF-SPA performs well at both site and regional scales, accurately simulating aircraft profiles of CO₂ concentration magnitudes (error <+- 4 ppm), indicating appropriate source sink distribution and realistic atmospheric transport. Hourly observations made at tall tower Angus were also well simulated by WRF-SPA (R² = 0.67, RMSE = 3.5 ppm, bias = 0.58 ppm). Analysis of CO₂ tracers at tall tower Angus show an increase in the seasonal error between WRF-SPA simulated atmospheric CO₂ and observations, which coincides with simulated cropland harvest. WRF-SPA does not simulate uncultivated land associated with agriculture, which in Scotland represents 36 % of agricultural holdings. Therefore, uncultivated land components may provide an explanation for the increase in model-data error. Interannual variation in weather is indicated to have a greater impact on ecosystem specific contributions to atmospheric CO₂ concentrations at Angus than variation in surface activity. In a model experiment, afforestation of Scotland was simulated to test the impact on Scotland’s carbon balance. The changes were shown to be potentially detectable by observations made at tall tower Angus. Afforestation results in a reduction in atmospheric CO₂ concentrations by up to 0.6 ppm at seasonal time scales at tall tower Angus. Detection of changes in forest surface net CO₂ uptake flux due to afforestation was improved through the use of a network of tall towers (R² = 0.83) compared to tall tower Angus alone (R² = 0.75).
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Patoka, Markus. "Improving Order Picking Processes through Proper Storage Assignment : Using results from previous mathematical research to simplify solving real life problems". Thesis, Högskolan i Borås, Akademin för textil, teknik och ekonomi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-11107.
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The area of order picking has been widely studied but still there is no general approach covering all the potential variables of a unique case. Optimizing the product placement is a useful way to improve order picking through reduced travel distances and goes hand in hand with an appropriate batching strategy and routing policy. The existing methods are of mathematical basis and can be costly to implement and it is therefore necessary to develop a non-mathematical approach that can be used for distribution centers and in this particular case, the warehouse of a mail order company. Literature is reviewed to investigate the current situation of a large Swedish mail order retailer for the development of a unique product assignment strategy, taking into consideration potential variables. It was found out that a lot of trade-offs are being done all the time between travel distances of the SKUs. Also, it was found out that “cart blocking” might be a potential problem when using a turnover-based storage assignment strategy.
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Cukrowski, Jacek y Manfred M. Fischer. "European Integration: Strategic Market Research and Industry Structures". WU Vienna University of Economics and Business, 2000. http://epub.wu.ac.at/3962/1/SSRN%2Did1435350.pdf.
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The paper is concerned with the impact of market research prior to integration, on
the structures of noncompetitive industries in integrated economy. The analysis focuses
on separated, single commodity, monopolistic markets with stochastic demand.
Monopolistic firms are considered in dynamic multiperiod model, where intertemporal
links are determined by expenditures on market research in a present period and benefits
from this activity (i.e., smaller variance of the prediction error) in the future. Assuming
that each firm maximizes its total discounted expected utility from profit in indefinite
time, we show that the optimal market research strategy is stationary and depends on
market size. Consequently, in the period following integration firms operating prior to
integration in small markets (such as Slovenia, Czech Republic, Hungary or Estonia) are
expected to have much less information about the integrated market than their
competitors operating before integration on European market. This informational
asymmetry may affect the structure of the industry in integrated economy. In the
extreme case, the firm operating before integration in the small market can be ruled out
from the integrated market. (authors' abstract)
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Silva, Ana Raquel Lucas e. "Equity Research - Altri SGPS S.A". Master's thesis, Instituto Superior de Economia e Gestão, 2015. http://hdl.handle.net/10400.5/9113.
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Mestrado em FinançasO objetivo deste estudo é saber se o valor da empresa no mercado está correcto ou está sobre ou subvalorizado. A informação obtida do mercado e da empresa neste estudo proporcionará a um investidor um maior conhecimento da indústria, ponderar riscos e ter uma perspectiva se deve comprar ou vender uma acção. Neste sentido estudou-se os principais métodos de avaliação recorrendo à literatura existente. Também se fez um estudo dirigido à industria da polpa de forma a entender as principais características da mesma, adoptando-se o estudo do passado ainda que recente e perspectivas futuras. Seguiu-se depois um estudo dos indicadores principais e a performance operacional da Altri. Estas análises contribuirão para assumir pressupostos relativamente ao cálculo do valor da Altri. Os resultados obtidos indicam um mercado com cash flow voláteis com um grau de incerteza elevado, ainda que tendo em conta o pouco conhecimento que existe da indústria.
In this project the ultimate objective is to value Altri SGPS, S.A. The information disclosed in this report will permit a wide knowledge about the industry and also consider risk involved. In order to do a good work it was conducted a study in the main methods to value a company using the literature existing which will support the work throughout the project. The analysis of the pulp industry contribute to perceive some opportunities in this market, to understand the cyclical behavior as a feature, and a massive contribute to make assumptions when forecasting the value of Altri SGPS, SA. The results indicate that the price of the share in a cyclical company is volatile and it has high values of uncertainty. If there is no perfect foresight about the industry cycles it is most likely to obtain a value that will not describe what might happen. Thus who has information will have an accurate price value.
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Tsang, Kwan-ming. "Application of operation research techniques for forecasting transportation demand, planning train services and station facilities of the MTRC". Hong Kong : The University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record/B42574717.
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Thoe, Wai y 陶煒. "A daily forecasting system of marine beach water quality in Hong Kong". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B46289100.
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Kummerow, Max F. "A paradigm of inquiry for applied real estate research : integrating econometric and simulation methods in time and space specific forecasting models : Australian office market case study". Thesis, Curtin University, 1997. http://hdl.handle.net/20.500.11937/1574.
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Office space oversupply cost Australia billions of dollars during the 1990-92 recession. Australia, the United States, Japan, the U.K., South Africa, China, Thailand, and many other countries have suffered office oversupply cycles. Illiquid untenanted office buildings impair investors capital and cash flows, with adverse effects on macroeconomics, financial institutions, and individuals. This study aims to develop improved methods for medium term forecasting of office market adjustments to inform individual project development decisions and thereby to mitigate office oversupply cycles. Methods combine qualitative research, econometric estimation, system dynamics simulation, and institutional economics. This research operationalises a problem solving research paradigm concept advocated by Ken Lusht. The research is also indebted to the late James Graaskamp, who was successful in linking industry and academic research through time and space specific feasibility studies to inform individual property development decisions. Qualitative research and literature provided a list of contributing causes of office oversupply including random shocks, faulty forecasting methods, fee driven deals, prisoners dilemma game, system dynamics (lags and adjustment times), land use regulation, and capital market issues. Rather than choosing among these, they are all considered to be causal to varying degrees. Moreover, there is synergy between combinations of these market imperfections. Office markets are complex evolving human designed systems (not time invariant) so each cycle has unique historical features. Data on Australian office markets were used to estimate office rent adjustment equations. Simulation models in spreadsheet and system dynamics software then integrate additional information with the statistical results to produce demand, supply, and rent forecasts. Results include models for rent forecasting and models for analysis related to policy and system redesign. The dissertation ends with two chapters on institutional reforms whereby better information might find application to improve market efficiency.Keywords. Office rents, rent adjustment, office market modelling, forecasting, system dynamics.
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Eguasa, Uyi Harrison. "Strategies to Improve Data Quality for Forecasting Repairable Spare Parts". ScholarWorks, 2016. https://scholarworks.waldenu.edu/dissertations/3155.
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Poor input data quality used in repairable spare parts forecasting by aerospace small and midsize enterprises (SME) suppliers results in poor inventory practices that manifest into higher costs and critical supply shortage risks. Guided by the data quality management (DQM) theory as the conceptual framework, the purpose of this exploratory multiple case study was to identify the key strategies that the aerospace SME repairable spares suppliers use to maximize their input data quality used in forecasting repairable spare parts. The multiple case study comprised of a census sample of 6 forecasting business leaders from aerospace SME repairable spares suppliers located in the states of Florida and Kansas. The sample was collected via semistructured interviews and supporting documentation from the consenting participants and organizational websites. Eight core themes emanated from the application of the content data analysis process coupled with methodological triangulation. These themes were labeled as establish data governance, identify quality forecast input data sources, develop a sustainable relationship and collaboration with customers and vendors, utilize a strategic data quality system, conduct continuous input data quality analysis, identify input data quality measures, incorporate continuous improvement initiatives, and engage in data quality training and education. Of the 8 core themes, 6 aligned to the DQM theory's conceptual constructs while 2 surfaced as outliers. The key implication of the research toward positive social change may include the increased situational awareness for SME forecasting business leaders to focus on enhancing business practices for input data quality to forecast repairable spare parts to attain sustainable profits.
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Shepherd, Tristan James. "A Numerical Modelling Study of Tropical Cyclone Sidr (2007): Sensitivity Experiments Using the Weather Research and Forecasting (WRF) Model". Thesis, University of Canterbury. Geography, 2008. http://hdl.handle.net/10092/2611.
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The tropical cyclone is a majestic, yet violent atmospheric weather system occurring over tropical waters. Their majesty evolves from the significant range of spatial scales they operate over: from the mesoscale, to the larger synoptic-scale. Their associated violent winds and seas, however, are often the cause of damage and destruction for settlements in their path. Between 10/11/07 and 16/11/07, tropical cyclone Sidr formed and intensified into a category 5 hurricane over the southeast tropical waters of the northern Indian Ocean. Sidr tracked west, then north, during the course of its life, and eventually made landfall on 15/11/07, as a category 4 cyclone near the settlement of Barguna, Bangladesh. The storm affected approximately 2.7 million people in Bangladesh, and of that number 4234 were killed. In this study, the dynamics of tropical cyclone Sidr are simulated using version 2.2.1 of Advanced Weather Research and Forecasting — a non-hydrostatic, two-way interactive, triply-nested-grid mesoscale model. Three experiments were developed examining model sensitivity to ocean-atmosphere interaction; initialisation time; and choice of convective parameterisation scheme. All experiments were verified against analysed synoptic data. The ocean-atmosphere experiment involved one simulation of a cold sea surface temperature, fixed at 10 °C; and simulated using a 15 km grid resolution. The initialisation experiment involved three simulations of different model start time: 108-, 72-, and 48-hours before landfall respectively. These were simulated using a 15 km grid resolution. The convective experiment consisted of four simulations, with three of these using a different implicit convective scheme. The three schemes used were, the Kain-Fritsch, Betts-Miller-Janjic, and Grell-Devenyi ensemble. The fourth case simulated convection explicitly. A nested domain of 5km grid spacing was used in the convective experiment, for high resolution modelling. In all experiments, the Eta-Ferrier microphysics scheme, and the Mellor-Yamada-Janjic planetary boundary layer scheme were used. As verified against available observations, the model showed considerable sensitivity in each of the experiments. The model was found to be well suited for combining ocean-atmosphere interactions: a cool sea surface caused cyclone Sidr to dissipate within 24 hours. The initialisation simulations indicated moderate model sensitivity to initialisation time: variations were found for both cyclone track and intensity. Of the three simulations, an initialisation time 108 hours prior to landfall, was found to most accurately represent cyclone Sidr’s track and intensity. Finally, the convective simulations showed that considerable differences were found in cyclone track, intensity, and structure, when using different convective schemes. The Kain-Fritsch scheme produced the most accurate cyclone track and structure, but the rainfall rate was spurious on the sub-grid-scale. The Betts-Miller-Janjic scheme resolved realistic rainfall on both domains, but cyclone intensity was poor. Of particular significance, was that explicit convection produced a similar result to the Grell-Devenyi ensemble for both model domain resolutions. Overall, the results suggest that the modelled cyclone is highly sensitive to changes in initial conditions. In particular, in the context of other studies, it appears that the combination of convective scheme, microphysics scheme, and boundary layer scheme, are most significant for accurate track and intensity prediction.
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Dern, Dean y 鄧之昌. "Taiwan stock index research and forecasting". Thesis, 1999. http://ndltd.ncl.edu.tw/handle/96268592853669288991.
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碩士國立政治大學
統計學系
87
The article utilizes the transfer function model in time series to make prediction on closing volume with closing value of the stock market, the American Dow Jones average index with the index of Taiwan stock market index, NASDAQ index with Taiwan electronic stock. In additional to discovering the appropriate prediction model, we can simultaneously see the influence of America with great economic power on Taiwan and how the concept that the volume determines the value is verified. During the process of this research, the outcome of the analysis indicates the closing volume is two times ahead of the closing value while the volume and value of the electronic and glamour stocks are changing in the same time and the American stock value and NASDAQ index are one time ahead of Taiwan electronic stock value. Besides the analysis based on the whole data, we can predict the possible futuristic stock trend. On the other hand, we can get pretty good result based on this theory, which accounts for the fact that America has some influence on Taiwan stock market and verifies the concept that the volume determines the value.. In addition, these three phenomenon can serve as the references for the prediction on the Taiwan stock index.
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Day, Min-Yuh y 戴敏育. "Research Of Applying Genetic Algorithms To Fuzzy Forecasting-Focus On Sales Forecasting". Thesis, 1995. http://ndltd.ncl.edu.tw/handle/98418171464602711307.
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碩士淡江大學
資訊管理研究所
83
The major purpose of this study is applying Genetic Algorithms(GAs) to developing fuzzy forecasting in order to increase the accuracy of forecasting. Genetic algorithm is a parallel goal-oriented search technique for optimization and can be used to easily find out the global or nearly global optima for optimization problems. In this study, we focus on sales forecasting and propose a dynamic forecasting model by using Genetic Algorithms in searching the optimal linguistic variables and partition intervals, and finding out the most fitness model basis w of fuzzy time series in different cases. Finally, we propose adding the expert opinions served as leading indicators in the fuzzy time series for forecsting value. Results show that the accuracy of the forecasting results is significantly improved, it proved the effectiveness of the fuzzy forecasting model we proposed.
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Monahan, Kayla M. "Aircraft Demand Forecasting". 2016. https://scholarworks.umass.edu/masters_theses_2/329.
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This thesis aims to forecast aircraft demand in the aerospace and defense industry, specifically aircraft orders and deliveries. Orders are often placed by airline companies with aircraft manufacturers, and then suddenly canceled due to changes in plans. Therefore, at some point during the three-year lead time, the number of orders placed and realized deliveries may be quite different. As a result, orders and deliveries are very difficult to predict and are influenced by many different factors. Among these factors are past trends, macroeconomic indicators as well as aircraft sales measures. These predictor variables were analyzed thoroughly, then used with time series and multiple regression forecasting methods to develop different forecasts for quarterly and annual orders and deliveries. The relative accuracies of forecasts were measured and compared through the use of Theil’s U statistic. Finally, a linear program was used to aggregate multiple forecasts to develop an optimal combination of all forecasts. In conclusion, the methods employed in this thesis are quite effective and produce a wholesome aggregate forecast with an error that is generally quite low for a forecasting task as challenging as this one.
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Yeh, Chih-Ming y 葉志明. "Research on the Short-Term Photovoltaic Power Forecasting". Thesis, 2011. http://ndltd.ncl.edu.tw/handle/xg65cb.
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碩士國立臺北科技大學
電機工程系研究所
99
Since the the signing of the Kyoto Protocol and the global efforts in reducing carbon emission, the green energy industry has been developing with great vitality in recent years. Taiwan in particular boasts a well-established solar energy industry. Characterized by advantages like easy installation and integration into buildings, low pollution, and the capability of lowering fossil fuel consumption, Solar energy relies on capturing and converting solar radiation into electricity. However, subject to the changes in season, time, weather, cloud amount and other external factors, solar radiation is marked with uncertainty as it is difficult to predict the energy output in the even the next hour. This inherent instability renders the prediction of energy output an especially crucial issue in the effective operation of solar power systems. This paper uses prediction methods including Time series analysis aims at measuring the correlation between data and identifying the special features of data to facilitate prediction. Back-propagation neural network is capable of performing effective prediction by analyzing nonlinear statistical data; The main essence of the Adaptive Neuro-Fuzzy Inference Systems solution is the use of fuzzy theory and neural network learning characteristics and thus enhance the prediction accuracy. The forecast data are historical data in Taichung, Penghu and Malaysia, and the solar energy capacities are respectively 72kW, 70kW and 45.36kW. The predicted results show that Adaptive Neuro-Fuzzy Inference Systems prediction error and low frequency high, because it can effectively be done for each input variable fuzzy classification, and learning by neural networks, fuzzy features that not only has the characteristics of neural networks, and strengthen the overall predicted structure. This will increase the forecast accuracy is relatively many, with the predicted structure, when the capacity increases to more accurately predict when the document generation. Simulation results show that in these five cases, ANFIS is more accurate the prediction error is about 3.8% accurate forecasts for the industry not only provides reference for the development towards a greater capacity, can also provide this information as an economic Taipower scheduling.
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Liu, Yu-Te y 劉昱德. "The Research on Flood Forecasting Based on Landmarks". Thesis, 2014. http://ndltd.ncl.edu.tw/handle/47278725109800838340.
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碩士國立臺灣海洋大學
資訊工程學系
102
The disaster brought by heavy rain has become more and more serious in Taiwan, and it has been an important research issue to provide warning messages before flood. In the past research, we have built a flood forecasting system based on the TwoFD module developed by hydraulic experts, but directly displaying all the flooded cells on maps might take a lot of time. Therefore, we propose to summarize flooded cells based on landmarks. Such messages will be short and clear, and we can evaculate the persons within the landmark in advance. To do this, the main research issue is how to find the effective warning message rapidly. We propose two methods. The VC method uses Voronoi diagram and R-tree to perform spatial join between flooded cells and the minimum bounding rectangle of landmarks' Voronoi cells, and then find the landmarks nearby flooded cells. We also propose the C2L method to pre-calculate the distance between cells and landmarks to preclude those cells whose distances are more than a given threshold. At the end, we have performed a series of experiments and used a variety of data sets to examine the effectiveness and the efficiency of our two methods. Experimental results show that although the C2L method requires more space for the pre-built indices, it performs better in terms of effectiveness and efficiency.
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Lin, Ping-wen y 林品妏. "Research on Tourism Demand Forecasting Using Grey Theory". Thesis, 2011. http://ndltd.ncl.edu.tw/handle/43274383524302654729.
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碩士國立雲林科技大學
全球運籌管理研究所碩士班
99
In recent years, the exchanges between cross-strait has been frequently as cross-strait relations develop peacefully. The People''s Republic of China (PRC) government encourages its people to make a tour to Taiwan also accelerate the number of Chinese tourists. This research uses Grey Theory to construct prediction model to the number of Chinese tourists to Taiwan. Taking the statistical data from February 2009 to January 2011 as samples, prediction of the number Chinese tourists to Taiwan is conducting. GM(1,1), grey seasonal model, grey markov residual modification model and exponential smoothingto do prediction. The results reveal that the combination of grey seasonal model and markov residual modification model has the highest accuracy. Base on the result of this research, related suggestions are given.
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Lin, Chih-hao y 林志豪. "Research on Grey Forecasting Model with Acceleration Characteristics". Thesis, 2009. http://ndltd.ncl.edu.tw/handle/74408483106238019927.
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碩士義守大學
工業工程與管理學系碩士班
97
From the past to now, human being is curious about the unknown future. Subsequently, numerous methods are developed to predict the future, from “Bagua (The Eight Diagrams)” of ancient China and “Astrology” of Babylon to the “Tarot” which is most popular in the present time. All the efforts are devoted to predict the future and try to avoid the disaster and get the fortune. Due to the development of mathematics and statistics, the forecasting science is a fast growing subject. In the recent years, there is an emerging forecasting method which is called “Grey Theory” proposed by Prof. Deng. The characteristics of the Grey theory are easy mathematics, less data needed and high prediction precision. Among the Grey theory, the Grey forecasting is one of the most popular subjects. The general case is GM(m,n) which m represents the order of differentiation and n represents the number of influencing factors. The GM(1,1) is the basic model and is applied to numerous research fields. The GM(2,1) is the research interest in this study because of its controversy in existence. In order to show its existence, the interpretation of GM(2,1) is introduced by considering physical point of view. And it is believed that GM(2,1) indeed exists and is suitable for system with acceleration or deceleration because of second differentiation appeared in the original equation. To prove our deduction correct, a set of raw data with periodical change is chosen and collected. The international cruel oil price obtains the characteristic of periodical change and its future trend is forecast both by GM(1,1) and GM(2,1) respectively. The result shows that GM(2,1) holds higher forecasting accuracy than GM(1,1) because of the periodical change essence in cruel oil price. Futhermore, the GM(2,1) is applied to forecast the domestic oil price and the result is also satisfactory.
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沈高毅. "The research of forecasting Taiwan stock index future". Thesis, 1998. http://ndltd.ncl.edu.tw/handle/84493255954398268484.
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陳至尚. "Gray system theory research in the rice price forecasting". Thesis, 2009. http://ndltd.ncl.edu.tw/handle/08189981099958546135.
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AI, SUN y 孫艾. "Research on Exchange Rate Forecasting Based on Information System Algorithm". Thesis, 2017. http://ndltd.ncl.edu.tw/handle/65v4u5.
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博士國立高雄應用科技大學
國際企業研究所
105
Abstract Along with the rapid development of financial globalization, our country faces complicated financial risks and foreign exchange risks. The subprime mortgage crisis, the sovereign debt crisis in areas with the euro, etc., spurred a global financial crisis and an economic recession and hence caused exchange rate prediction to evolve into an important economic issue, drawing wide attention. However, the foreign exchange market is a non-linear system with multiple variables, in which correlations between all factors are perplexing, exacerbating the difficulty of exchange rate prediction. As a complex non-linear system, exchange rate prediction methods have developed into a time series prediction from a parametric regression. However, in real applications, exchange rate fluctuations and varying trends are very complex, and the execution speed of the algorithm must surpass the variation speed of exchange rate at the same time as the exchange rate is precisely predicted. Although numerous studies pertaining to exchange rate prediction methods are currently available, the majority of the algorithms have been constrained by their complexity, and relevant research analysis has not been conducted on the applicability to data sets of the algorithms commonly used in exchange rate prediction. On account of this, three major method types are selected in this dissertation as the methodological basis of the research: the algorithm based on the empirical risk minimization principle, the algorithm based on the structural risk minimization principle, and the statistical filtering algorithm. Methods representative of algorithms theoretically applicable to exchange rate prediction are separated from the three major methods, namely, the Radial Basis Function Neural Network (RBFNN), the Least Squares-Support Vector Machine (LS-SVM), and the Kalman Filter (KF). The three methods mentioned above are selected in this dissertation to represent the three major methods, and explore their precision, efficiency, and applicability concerning exchange rate prediction. In addition, we contrast the three major types of algorithms according to test results, analyze the applicability of the different algorithms to data sets, and offer a novel train of thought and technological research on solving the problem of exchange rate prediction. The main sections of the dissertation are as follows: 1. The widely-used type of neural network, RBFNN, is introduced into the field of exchange rate prediction based upon the empirical risk minimization principle. This method both inherits the empirical risk minimization principle and introduces the kernel functions of RBF, has a higher prediction accuracy, simple structure, fast training speed, and different from the ordinary feedforward neural networks, with the best approximation performance and overall optimization. 2. This dissertation takes LS-SVM to represent the methods based on the structural risk minimization principle used for exchange rate prediction, since the methods based on the empirical risk minimization principle have lower prediction accuracy in circumstances of insufficient data. Addressing the issue of slower computation and convergence speeds of the traditional SVM algorithm, this method solved the problem of quadratic programming with LS on the premise of ensured minimal structural risks. Therefore, adopting this method may ensure the accuracy of the algorithm in cases of small sample size, as well as completing the prediction faster. 3. Addressing the deviation existing in both the prediction results from each type of method and in the exchange rate data, this dissertation proposes an exchange rate method based on the Kalman Filter. This method is representative of statistical filtering algorithms and may internally reduce noise in the two models to acquire more accurate prediction values. Therefore, adopting this method may effectively utilize the accuracy of the two models and allow the acquisition of more precise prediction values by statistical means.
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Fan, Chich-Kai y 范智凱. "Research of a Fault Forecasting System for Wind Power Generation". Thesis, 2013. http://ndltd.ncl.edu.tw/handle/82177291510882172448.
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碩士國立勤益科技大學
電機工程系
101
This paper propose a new method to forecast wind power generation fault, it is able to diagnose the fault omen of wind power system before accident, and change the operating status of the wind power system in advance, so it would effectively avoid serious destruction in the system. First, the proposed scheme uses a series of sensor to derive important characteristic data from the wind power system, and then stored in the database. To detect small change, we propose using chaos synchronism-based detect method to form chaos error spreading figures, and use the key point of spreading figure to be the characteristic of fault diagnosis, so that it would reduce the amount of characteristics. Second, we use gray prediction method to predict change trajectory of characteristics, it can predict the next cycle of characteristic data. We use extension identified method to diagnose the fault of wind power system, to change the operating status of the wind power system in advance and to implement emergency action, so it would effectively avoid serious destruction in the system, and highly reduce the repairing time and operating cost.
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Yang, Ching-Wen y 楊靜汶. "The Research of Forecasting Model of Global IC Industry Supply". Thesis, 2009. http://ndltd.ncl.edu.tw/handle/90554048844916134717.
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碩士清雲科技大學
國際企業管理研究所
97
A procedure is The production forecasting of high technology industries is an important issue for entrepreneurs and governments, but it suffers from the situation of fast growth and frequent fluctuation. This article provides forecasting performance by using Bayesian vector autoregression (BVAR) forecasts. The BVAR model possesses the superiority of Bayesian statistics in small sample forecasting and holds the dynamic property of VAR (Vector autoregression) model. We examined the production value/sales annual growth rate of global semiconductor industry from 1979 to 2002 by using some leading indicators. In our methodology processing, first, we divide our data into some cycles and use them to test our model by using the twelve-steps ahead forecasting. Second, according to the history data, we forecast the production value/sales of global semiconductor industry for the next two years. Our results show that, the non-informative prior BAVR model can approximately match each trend of these cycles. We also show that we could exactly find the inflection point of the trend and give a promising forecasting. From these trends, we conclude that the production value/sales of global semiconductor industry will grow over the next two years.
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Yang, Ssu Hui y 楊斯惠. "The research on travel time forecasting of freeway freight vehicle". Thesis, 2010. http://ndltd.ncl.edu.tw/handle/36687513081722365291.
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碩士德明財經科技大學
經貿運籌管理研究所
98
Due to the Electronic Toll Collection and Traffic Control System has been constructed in Taiwan; Freeway Bureau has already provided travel time prediction data which be calculated from the traffic speed collected by these two systems. The better utilization of this information could improve freight vehicle company efficiency in time, reduce the travel cost and make the right route choices. The methodology of Freeway Bureau prediction model is linear regression. However, its weight values were assigned by rule of thumb and without validating. So, this research wants to validating this empirical model and calculating its weight values. The traffic speed and travel time data of Freeway No.1 northbound, from 35 KM to 71 KM, dated from February 2 to February 27, 2009 which be collected from electronic toll system and vehicle detectors were used for analysis. The MAPE value of the reconstructed model is about 11% , when using the data of freight vehicles to estimate travel time. This research would be helpful for the government and freight vehicle companies to predicting the freeway travel time.
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Liao, Fan-Yu y 廖凡宇. "The Research of Stock Price Forecasting Based on Neural Network". Thesis, 2010. http://ndltd.ncl.edu.tw/handle/7md3bp.
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碩士國立虎尾科技大學
資訊管理研究所
98
In this era, information is easily acquired. In recent years, moving towards liberalization and internationalization on the domestic stock market attracts more investors. Due to fast change in economic environment, the risk to invest in the stock market is getting higher. As the trend of the stock price is difficult to predict, investors must consider the following four points: 1. How to properly select stock is one of the goals that investors pay attention to 2. What is the correct timing to buy stock 3. Prepare a transaction tactics for stock purchase and sell 4. Set up the options for stock investment. In the past, many researches were undertaken by utilizing neural networks, like: junk email filtering, agricultural products sales prediction, including stock market prediction. There still remains space for improvement and we continue to carry on research in this respect. This research focuses on Taiwan 50 (ETF50) for historical database of the stock, and employs neural network with the eight technological analysis indicator of investment (KD, RSI, MA, MACD, William''s indicator, AR&BR, MTM, TAPI) to build the intelligent prediction of stock market trend. Hopefully this will help investors to make correct judgment in stock market sales and reduce the investment risk.
47
De, Wet A. J. C. "Investigating fashion forecasting approaches in South Africa : proposed way forward". Thesis, 2012. http://hdl.handle.net/10210/5211.
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M.TechThis study is an investigation into current local and international fashion forecasting approaches and procedures, as well as to discover whether intuition has relevance in the forecasting process. South African fashion is currently in the process of transformation; discovering and establishing a fashion identity, after decades of unquestioningly following international fashion trends (Chang, 2005:20; Cohen, 2005:27; Levin, 2005a: 75-78). The emergence of local fashion/trend forecasting practices in recent years is part of this transformation process. An underlying assumption of this study is that South African fashion will continue to develop, resulting in an increasing demand for fashion forecasting in the country. As there are currently no guidelines available, the study aims to provide insight into a way forward for this practice in South Africa. The study is grounded within a qualitative research paradigm, and the research design and data collection methods have accordingly been selected. The chosen research design falls largely within the framework of an ethnographic study. A comprehensive analysis of existing literature was conducted in order to provide a theoretical grounding to the study and to acquire a global perspective on forecasting procedures. This was followed by semi-structured interviews to obtain primary data from a South African perspective. The participants were purposely selected according to set criteria. The first criteria for selection required the participants to be leading role-players in their particular fields. Secondly, individuals who are trend forecasters by profession, as well as those who may use forecasting material in their businesses. Thirdly, the sample of participants represents specified sectors within the South African fashion/lifestyle industries. Namely, editors at leading trend magazines, in-house trend forecasters/analysts at leading fashion retailers, designers and independent trend analysts/forecasters. In order to construct the findings of the study qualitative content analysis was used as the method for data analysis. Through this process, the descriptions of the participants were interpreted to establish commonalities in practice, so as to identify viable threads of relevance regarding trend forecasting within a South African context. The research findings narrate the participants’ experiences within the field of trend/fashion forecasting, their knowledge frameworks being key to the study (Henning, van Rensburg & Smit, 2004:19). It is evident from the findings that the practice of fashion forecasting in South Africa is at an early stage of development and therefore at present, limited procedural IV structures seem to be in place. The findings further indicate that intuition indeed plays a significant role in the forecasting process, and is often associated with insightful trend/fashion forecasting. South African fashion, although facing several challenges, is perceived to have enormous potential for growth and to be a successful international marketing commodity in the future. In order for the practice of fashion forecasting to be successful in the country, though, it needs to be approached with insight and integrity, and with a true intention to add value.
48
Lin, Tsang-Long y 林倉龍. "The Research of Forecasting Tourists in National Scenic Area in Taiwan". Thesis, 2004. http://ndltd.ncl.edu.tw/handle/5qp23d.
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碩士朝陽科技大學
休閒事業管理系碩士班
92
The government promote domestic tourism actively in recent years. Among the 2008-challenge the future plan, the domestic tourism development plan hope by submitting tourist double plan, package travel and new developing scenic area to Increase domestic tourists from 74 million to 1.5 hundred million. This study utilize Box-Jenkins’s ARIMA model and Ordinary Least Square Model to establish practical forecasting model for four area, north, central, south and east. Then assembly by forecasting combination method to evaluate the forecasting accuracy. The result shows that forecasting combination can improve the accuracy because it combine two models’ merit. In this study, unfortunately, due to the OLS shortcoming, it becomes barely outcomes. The North, Central and South area still remain more accuracy in ARIMA model forecasting value, only East area acquire more accuracy by the forecasting combination B. The result also shows the Tourists of National Scenic Area increase but slowly. The total tourist of National Scenic Area will reach 20 million in 2005 which is only 10% progress by 2003.
49
HUANG, CHIEN-LUNG y 黃建隆. "Research on Estimating and Forecasting Models of PV Power Generating System". Thesis, 2017. http://ndltd.ncl.edu.tw/handle/9dg26f.
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碩士國立高雄應用科技大學
電機工程系博碩士班
105
The capacity of PV Power Generating system has increased in the past years, but meanwhile 95% of the real time operation status information for the PV Power Generating system was never used for the power coordination Taiwan Power Company. However, for extremely low operating reserve, this information will be the key factor for stabilizing the system. Also according to current promoted policy and forecast, the PV Power Generating system will be expanded to 20GW; while if most of the private PV Power Generating system can’t share the real time generation status with control center, the cost and risk for the whole power net system would be high. This thesis will establish a simulation model, based on limited PV Power Generating generator sets to estimate the capacity of whole PV Power Generating system. In this way, the reserve could be monitored in real time and help Dispatch center of Taiwan Power Company to manage the whole solar system. Meanwhile, the PV Power Generating generation data will be collected in hour base. And an analysis will be performed and compared with those parameters for PV Power Generating system. Liner regression analysis will be applied with Least Square approach to establish the model for prediction, and by various verification processes, the reliability for this model can be confirmed. Finally, the prediction based on this model will be compared to the actual load from the system to identify the accuracy and effectiveness.
50
Yao, Jau Chang y 姚朝昶. "The Research on the Design of Earnings Forecasting Decision pport System". Thesis, 1993. http://ndltd.ncl.edu.tw/handle/42305371405396187891.
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