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Dissertations / Theses on the topic 'Short-term'
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1
Li, Li. "Short-term and long-term evolution of lentiviruses." Thesis, University of Nottingham, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.575475.
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Lentiviruses have paradoxically fast short-term rate of evolution and slow long-term rate of evolution, which differ by several orders of magnitude. In this thesis, with a new method called truncated tree analysis, slower rates of evolution of transmitted viruses were estimated. However, the rate decline of the transmitted viruses is limited, and is not sufficient to explain the dramatic difference between the short-term and long-term evolutionary rates. These dramatically different rates were reconciled by an S shaped curve based on the new trend observed from this thesis. In the middle part of this new trend, the rate of evolution decreases as the time of divergence increases. Using this new trend, the time scale of HIV -1 and their closest related SIV found in apes were set. The SIV cpzPtt and SIV cpzPts isolated from the two subspecies of chimpanzees shared the most recent common ancestor around 25.2 thousand years ago. This is younger than the estimated date of these two host subspecies split, and suggests that the SIV cpz is relatively new to the chimpanzees. The second chapter of this thesis further explores lentiviral evolution by examining the feline immunodeficiency viruses (FIV's). An American origin scenario of the FIV s was proposed. In this scenario the ancestor of FIV first the invaded the ancestors of the puma lineage living in American, and then as the ancient puma lineage speciated and migrated FIV spread out to many other felids. The final chapter of this thesis further explores the evolutionary rate decline as the time span extends by introducing the idea of flip- flop sites that undergo negative frequency dependent selection pressures. Theoretical simulations confirmed that in the short time span, the presence of the flip-flop sites results in overestimation of the evolutionary rate, but in longer time spans, opposite effects of flip-flop sites were observed.
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Ericson, Torgeir. "Short-term electricity demand response." Doctoral thesis, Norwegian University of Science and Technology, Department of Electrical Power Engineering, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-1484.
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Futter, Mark R. "Predicting short term flood risks." Thesis, University of Newcastle Upon Tyne, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.315639.
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Two models for estimating the short term risk of a flood exceeding some critical flow, which take account of the season and prevailing conditions have recently been published. The model proposed by Ettrick (1986) is based on conditional probability distributions, while Smith and Karr (1986) relate the rate of exceedence of the critical level of interest to relevant covariates. Both models are fitted to a 1000 year synthetic data set, to compare the results with empirically derived immediate and 30 day ahead risk estimates. After some modifications to the Smith and Karr model, both models demonstrate reasonable accuracy. A second comparison is then made using summer data from a U.K. catchment. The results demonstrate the sensitivity of the risk to the prevailing conditions at the beginning of the period of interest. The assumptions, data requirements and accuracy of the models are compared and discussed. The Ettrick model is chosen for further consideration, given that this model is based on a precipitation threshold, whilst the Smith and Karr model is based on a flow threshold, and the data record is longer for the former. The Ettrick model is then applied to two other U.K. catchments to give all year flood risk estimates. These cover the immediate, 7 day and 30 day ahead time periods. For the immediate flow risk estimates, the importance of snow on the catchment to the levels of flood risk is highlighted. In the case of the 7 day ahead estimates, the significance of the snow is reduced. Given this latter result, the 30 day ahead estimates are not conditional on snow, but still highlight a strong seasonality in the flood risk. Application of the Ettrick model is shown to imply the variable source area concept of runoff production. This may not be the dominant runoff production mechanism on certain catchments, and as such, restricts applicability of the Ettrick model.
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ESTEVES, GHEISA ROBERTA TELLES. "SHORT TERM LOAD FORECASTING MODELS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2003. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=3715@1.
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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOAplicação de duas metodologias, para prever e modelar o comportamento de uma serie temporal de carga de energia elétrica, a serie histórica de carga elétrica horária de uma das concessionárias de energia elétrica do sudeste brasileiro, a ESCELSA. Foram aplicadas as metodologias de amortecimento direto, e uma metodologia recente, o método de Holt-Winters com múltiplos ciclos. Ambas as metodologias são utilizadas para fazer previsão horária de carga de energia elétrica, portanto, é feita, previsão 24 passos a frente.
Application of two diferent metodologies, in order to model and forecast the behavior of time series of hourly electrical loads generated by ESCELSA. Was applied to the time series studied the metodology of the direct smoothing, and also a recent metodology, the Holt-Winters with multiple sazonalities. In both of them it has been done the hourly forecast (24 hours load forecasting).
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Bai, Xiwen. "Forecasting short term trucking rates." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117796.
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Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2018.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged student-submitted from PDF version of thesis.
Includes bibliographical references (pages 79-83).
Transportation costs constitute an important part of total logistics costs and have a dramatic impact on all kinds of decisions across the supply chain. Accurate estimation of transportation costs can help shippers make better decisions when planning transportation budgets and can help carriers estimate future cash flows. This study develops a forecasting model that predicts both contract and spot rates for truckload transportation on individual lanes for the next seven days. This study considers several input variables, including lagged values of spot and contract rates, rates on adjacent routes and volumes. The architectural approach to short-term forecasting is a neural network based on Nonlinear Autoregressive Models with eXogenous input (NARX) models. NARX models are powerful when modelling complex, nonlinear and dynamic systems, especially time series. Traditional time series models, including autoregressive integrated moving average (ARIMA), are also used and results from different models are compared. Results show that the NAR model provides better short-term forecasting performance for spot rates than the ARIMA model, while the ARIMA model performs slightly better for contract rates. However, for a longer-term forecast, the NARX model provides better results for contract rates. The results from this study can be applied to industrial players for their own transportation rate forecasting. These results provide guidelines for both shippers and carriers regarding what model to use, when to update the model with new information, and what forecasting error can be normally expected from the model.
by Xiwen Bai.
M. Eng. in Supply Chain Management
6
Olieman, J. F. "Infantile Short Bowel Syndrome: short and long term evaluation." [S.l.] : Rotterdam : [The Author] ; Erasmus University [Host], 2009. http://hdl.handle.net/1765/14961.
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Gohil, Risha. "Short term physiological changes secondary to exercise in intermittent claudication : short term physiological changes in claudication." Thesis, University of Hull, 2013. http://hydra.hull.ac.uk/resources/hull:10090.
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Background: In patients with intermittent claudication (IC), supervised exercise programmes (SEP) improve walking distance and quality of life (QoL); however the mechanisms by which these benefits are achieved remain unclear. Endothelial dysfunction is recognised as a trigger of the atheroinflammatory cascade and subsequent cardiovascular disease. In health, training improves cardiorespiratory physiology, inflammation and endothelial function. Changes in cardiorespiratory physiology, inflammatory markers and endothelial function are contradictory in IC. Objectives: This thesis aimed to assess the impact of SEP on cardiopulmonary physiology, endothelial function and athero-inflammatory markers in patients with IC. Methods: Following local research ethics committee and R & D approval, patients with IC were recruited from outpatient clinic. After providing informed written consent, patients underwent baseline assessment on two separate days. Session 1: participants completed a constant load treadmill test with pre and post exercise ankle brachial pressure indices. Session 2: measured QoL, endothelial function (EndoPAT2000, Itamar, Israel), venepuncture and a cardiopulmonary exercise test (CPET) using cycle ergometry. Participants then underwent a 12 week period of SEP which consisted of circuit training, with re-assessments at six and twelve weeks. The primary outcome measure was a 1.5ml/kg/min improvement in peak VO₂ after six weeks of exercise. Secondary outcomes included changes in endothelial function, quality of life, walking distance and inflammatory markers at both six and twelve weeks. Results: No significant improvements in CPET measurements, endothelial function or inflammation were demonstrated at any time point. Traditional markers of walking ability and QoL demonstrated an improvement by 12 weeks. Conclusions: The underlying mechanism through which exercise improves walking distance remains un-identified. Further work regarding the changes at the cellular level within the muscle is of importance.
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Wang, Yang. "Modeling of Ultracapacitor Short-term and Long-term Dynamic Behavior." University of Akron / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=akron1217029983.
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Estalrich-Lopez, Juan. "Short-term operation of surface reservoirs within long-term goals." Diss., The University of Arizona, 1989. http://hdl.handle.net/10150/184854.
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A stochastic dynamic programming model (called P.B.S.D.P.) based on the consideration of peak discharge and time between peaks as two stochastic variables has been used to model and to solve a reservoir operation problem. This conceptualization of the physical reality allows to solve, in this order, the tactical and strategic operation of surface reservoirs. This P.B.S.D.P. model has been applied to the Sau reservoir in the Northeastern corner of Spain. The results showed a significant improvement over the currently used operation procedure, yielding values of yearly average electricity production that are somewhat under 6% of what could have been the maximum electricity production.
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Jassim, Aimon. "Short-term train crew rescheduling problem /." Leeds : University of Leeds, School of Computer Studies, 2008. http://www.comp.leeds.ac.uk/fyproj/reports/0708/Jassim.pdf.
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Henson, Richard Nevill Astley. "Short-term memory for serial order." Thesis, University of Cambridge, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.396139.
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Balmer, L. "Short term spectral estimation with applications." Thesis, University of Warwick, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.373072.
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SOARES, LACIR JORGE. "ESSAYS ON SHORT-TERM LOAD FORECASTING." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2003. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=4438@1.
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A previsão de carga é considerada uma poderosa ferramenta
no controle e planejamento de sistemas elétricos. Um grande
número de pesquisadores têm sugerido, recentemente,
diversas técnicas para previsão de carga a curto prazo.
Este trabalho estuda a aplicabilidade de modelos lineares.
O trabalho pretende ser uma base para uma aplicação real de
previsão. Os modelos foram desenvolvidos e testados com
dados reais de carga de uma empresa de eletricidade situada
no sudeste de Brasil. Todos os modelos são propostos para
dados secionais, isto é, a série de carga de cada hora é
estudada separadamte como uma série única. Esta abordagem
evita a modelagem de padrões intra-dia (perfil da carga)
complexos apresentados pela série de carga, que variam
durante os dias da semana e nas estações. Três modelos são
estudados, primeiro um modelo um modelo SARIMA ajustado por
variáveis binárias DASARIMA, adotado como modelo de
referência, o segundo um modelo em duas etapas que
considera a existência de componentes determinísticos para
modelar a tendência, a sazonalidade e os efeitos do
calendário, denominado modelo autorregressivo sazonal em
dois níveis - TLSAR; e o último um modelo de de memória
longa generalizada ajustado por variáveis binárias - DAGLM.
Os resultados dos ensaios mostraram que os modelos horários
são bem apropriados para uma aplicação de previsão. Os
erros de previsão, das duas últimas abordagens, são menores
que os do modelo de referência, DASARIMA. O trabalho sugere
que este tipo de modelos horários devem ser testados mais
completamente a fim de fornecer uma opinião final sobre sua
aplicabilidade.Load forecasting has been considered a powerful tool in managing and planning power systems. Several tecniques have been recently suggested for short-term load forecasting by a large number of researchers. This work studies the applicability of linear models in the area is intended to be a basis for a real forecasting application. The models were developed and tested on the real load data of a utility company located in the southeast of Brazil. All models are proposed for sectional data, that is, each hour's load is studied separately as a single series. This approach avoids modeling the intricate intra-day pattern (load profile) displayed by the load, wich varies throughout days of the week and seasons. Three models are studied, the first one a Dummy-Adjusted Seasonal Integrated Autoregressive Moving Average model - DASARIMA, acting as a benchmark, the second a two-step modeling that makes use of deterministic components to model trend, seasonality and calendar effects, called Two-Level Seasonal Autoregressive model - TLSAR; and the last one a Dummy-Adjusted Generalized Long Memory model - DAGLM. The test results showed that the hourly models are well suitable for forecasting application. The forecasting errors of the last two approaches were smaller than those of the DASARIMA benchmark. The work suggests that this kind of hourly models should be implemented in a through on-line testing in order to provide a final opinion on its applicability.
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Melly, Nicholas Kipchirchir. "Short-term solar forecasting for microgrids." Thesis, Melly, Nicholas Kipchirchir (2019) Short-term solar forecasting for microgrids. Masters by Coursework thesis, Murdoch University, 2019. https://researchrepository.murdoch.edu.au/id/eprint/51339/.
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This thesis explores the need and application of short-term solar forecasting (STSF) in microgrids. Among several solar forecasting methods, a justification for the choice of sky imaging tools as a preferred method for STSF in microgrids is provided.
The rapid increase in the uptake of solar PV in the electricity grid has shown a convergence in research in the fields of solar forecasting and management of the electricity grid. This energy transition from fossil fuel powered generation to renewable energy generation characterised by consumer-controlled energy generation and the emergence of smart grid has created a surge in demand for real time solar PV forecast information. The relationship between short-term solar forecasting information and microgrid PV generation fluctuation is analysed together to identify areas for the application of STSF technique in microgrid management.
To achieve this, the various solar forecasting methods are discussed with a view of identifying suitable techniques for microgrid applications. Sky imaging is identified as a preferred method thus the operation principle of a sky imaging tool is explained followed by analysis of capabilities of several tools/products available in the market. A summary chart showing the capabilities of WobaS, Steady eye, Instacast and CloudCAM STSF tools is presented in a table.
Three case studies are selected to demonstrate the need and application of STSF under the following scenarios:
• Case 1: Uncontrollable distributed energy resource for this case solar PV, together with centrally located fossil fuel powered power plant with no STSF tool in use.
• Case 2: Centrally located and controllable solar PV plant, a central fossil fuel power plant and energy storage using STSF tool.
• Case 3: Virtual power plant using STSF tool.
Through this approach the need, application and associated benefits of STSF is clearly shown. The benefits in cost savings for the combination of STSF with battery storage is demonstrated. Overall this thesis connects STSF and microgrid management.
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Cumming, N. "The Hebb effect : investigating long-term learning from short-term memory." Thesis, University of Cambridge, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.598214.
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How do we learn a sequence of items so we can remember it not only over the short-term, as in hearing a phone-number and repeating it back, but over the long term? Ten experiments are presented that investigate this problem using the Hebb repetition effect (Hebb, 1961). In a canonical Hebb effect experiment, lists of familiar items are presented in an immediate serial recall task and one list is repeatedly presented at regular intervals. This leads to an improvement in recall for the repeating list over baseline performance. Existing models of serial order learning are tested; Chapter 2 provides evidence contrary to positional models of the Hebb effect while Chapter 5 provides evidence against chaining models. The experiments in these chapters (Experiments 1, 2 and 7) use a transfer design where a representation of the repeating list (Hebb list) is built up, then a list is presented whose structure is derived from the Hebb list in a way that tests the predictions of these models. The experiments of Chapters 4 and 5 examine the hypothesis that the most parsimonious model of the Hebb effect is one that is based on the formation of chunks (Miller, 1956), higher-level representations of several items. The results of these experiments are consistent with a chunking model based on the Primacy model (Page and Norris, 1998), but do not provide direct evidence of a chunking process. A growing body of evidence (e.g. Baddley et al., 1988; Papagno et al., 1991) suggests that the phonological store of the working memory model (Baddeley, 1986) plays an important role in the development of long term representations required for the acquisition of new vocabulary. For example, the ability to learn new words is impaired in patients with damage to the phonological store (e.g. PV, SC) and in normal subjects performing articulatory suppression. In chapter 6, the hypothesis that the Hebb effect is an experimental analogue of phonological form learning is investigated, the results of which suggest that the Hebb effect is involved in at least some of the same processes.
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Wargentin, Robin. "Long-term and Short-term Forecasting Techniques for Regional Airport Planning." Thesis, KTH, Matematisk statistik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-190839.
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The aim of this thesis is to forecast passenger demand in long term and short term perspectives at the Airport of Bologna, a regional airport in Italy with a high mix of low cost traffic and conventional airline traffic. In the long term perspective, time series are applied to forecast a significant growth of passenger volumes in the airport in the period 2016-2026. In the short term perspective, time-of-week passenger demand is estimated using two non-parametric techniques; local regression (LOESS) and a simple method of averaging observations. Using cross validation to estimate the accuracy of the estimates, the simple averaging method and the more complex LOESS method are concluded to perform equally well. Peak hour passenger volumes at the airport are observed in historical data and by use of bootstrapping, these are proved to contain little variability and can be concluded to be stable.Målet med denna uppsats är att prognosticera passagerefterfrågan i lång- och kortsiktigt perspektiv på Bologna Flygplats, en regional flygplats i Italien med hög mix av lågkostnadsbolag och konventionella flygbolag. I det långsiktiga perspektivet appliceras en tidsseriemodell som prognosticerar hög tillväxt i passagerarvolymer på flygplatsen under perioden 2016-2026. I det korta perspektivet uppskattas efterfrågan utefter tid i veckan med hjälp av två icke-parametriska modeller; local regression (LOESS) och en simpel metod som beräknar medelvärdet utav observationer. Med cross validation uppskattas precisionen i modellerna och det kan fastställas att den simpla medelvärdesmetoden och den mer avancerade LOESS-metoden har likvärdig precision. Passagerarvolymer på flygplatsen under högtrafik observeras i historisk data och med hjälp av bootstrapping visas att dessa volymer har låg variabilitet och det kan fastställas att de är stabila.
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Tsiu, Matsepe Modikeng Theodore. "Testing the Long-Term Profitability of the Short-Term Reversal Strategy." Master's thesis, Faculty of Commerce, 2019. https://hdl.handle.net/11427/32074.
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The purpose of this investigation was to test the theoretical possibility of an investor earning a positive cash return from the activities of the stock market despite effectively holding no position at all in said market. The sample data were the daily returns for the shares of the 780 companies listed on the NASDAQ and the New York Stock Exchange (“NYSE”), which fell within the top 500 listed companies by market capitalisation between 1 January 2005 and 31 December 2017. The reversal strategy’s performance was evaluated using portfolios constructed as quantiles of 100 or 500 shares, respectively, where the investor had the option of implementing the reversal strategy immediately after an information-gathering period closed or a day thereafter. The time intervals used were 1 January 2005 to 29 September 2008 (the day the Dow Jones Industrial Average crashed by 777.68 points), 29 September 2008 to 31 December 2017 and 1 January 2005 to 31 December 2017. Of the 1000 portfolios tested in each time interval, at least 416 had positive average returns in every time interval. Of the portfolios that had positive average returns over the time intervals, at least 66 had statistically significant average returns in every time interval. The best-performing portfolio for the entire sample period was a combination of the best-performing pre-crash and post-crash portfolios - an investor who held that portfolio realised a cumulative return of approximately $61.39 for every $1 invested. The conclusion was that it was theoretically possible for an investor to earn a positive cash return from the market’s activities despite effectively holding no position at all in the market. Consequently, it was concluded that the strong form of Fama’s (1970) Efficient Market Hypothesis was disproved. Future research should include out-of-sample tests, tests that include restrictions on short selling and tests that consider the impact of trading costs on portfolio performance, to render the conclusions of this investigation more practically applicable to investors.
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Kalm, Kristjan. "Chunk formation in verbal short term memory." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.609987.
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Alexander, Justin. "Short-Termism and Corporate Myopia: The Values Assigned by the Market to Short-Term and Long-Term Firms." Scholarship @ Claremont, 2017. http://scholarship.claremont.edu/cmc_theses/1499.
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Short-termism and myopia on the part of corporate managers, analysts, and investors have created a business environment driven by the excessive focus on short-term results and the need to meet earnings targets at the expense of long-term value creation. These are accompanied by numerous consequences, including the potential for short-term-oriented firms, particularly in the U.S., to lag behind global long-term-oriented firms, as well as the potential for short-term mindsets in the corporate world to catalyze financial crises. In this paper, I demonstrate that the market generally assigns higher values to long-term firms rather than short-term ones. This is evidenced by the fact that firms characterized to be long-term according to various financial metrics have higher valuation multiples than their short-term counterparts. The results suggest that the market has a degree of sophistication that rewards investments for the future rather than earnings management and present gratification, and that the corporate world should therefore increasingly develop a long-term mentality.
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Öhman, Jesper, and Knut Benson. "How Short-term Leasing Can Mitigate Vacancies in Retail Stores : Implementing Short-term Leasing in the Retail Industry." Thesis, KTH, Fastigheter och byggande, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-297782.
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Retail is changing. E-commerce is increasing its percentage of total sales while physical storesare closing. This affects how real estate companies work with retail spaces to minimizevacancies, and short-term leasing, also called pop-up stores, is one way to do so. Pop-ups haveexisted in different forms for a very long time. Seasonal stores and farmers markets are twoexamples. The modern-day pop-up, assessed and discussed in this study, is the one not alwaysused for sales purposes but also marketing purposes. This study aims to see how modern-daypop-ups can fill the void left by rapidly closing retail stores.The study was carried out by reviewing existing literature about pop-ups and how they work,followed by semi-structured interviews with real estate companies and consultants throughoutthe property industry. Emphasis was put on bottlenecks and problems with implementing shortterm leasing and how market platforms can aid real estate companies with this.The study shows that real estate companies and the industry as a whole are aware of the statusof traditional retail and that they have started to use short-term leasing to a greater extent thanbefore. The real estate companies were positive towards using short-term leases as a tool tominimize vacancies. However, it also shows some problems with implementing short-termleases from a real estate company's perspective. The main obstacles found during the studywere transparency issues regarding vacant spaces, how short-term leases can negatively affectproperty values, and the time-consuming aspect of signing short-term contracts. Concludingthat market platforms can solve certain problems regarding short-term leases, but others haveto be solved by the real estate industry itself.Detaljhandeln genomgår en förändring. För varje år som går ökar e-handelns andelav detaljhandelns försäljning och antalet butiksvakanser blir allt större. Detta påverkar hurfastighetsbolag jobbar med sina butiksytor för att minimera det ökade antalet vakanser. Etttillvägagångssätt är att arbeta med korttidsuthyrningar, så kallade pop-up butiker. Pop-upbutiker har funnits väldigt länge och i olika former, så som säsongsbutiker och lanthandel. Denmoderna typen av pop-up butiker som kommer tas upp och diskuteras i denna uppsats är dockden som inte alltid är till för att maximera försäljning utan också för att använda imarknadsföringssyfte. Denna studie syftar till att undersöka hur moderna pop-up butiker kanhjälpa till att fylla det vakuum som lämnats av ett ökat antal vakanta butikslokaler.Uppsatsen skrevs genom en litteraturstudie av existerande litteratur om pop-up butiker samtsemistrukturerade intervjuer med fastighetsbolag och konsulter inom fastighetsbranschen. Härlades stor vikt vid de flaskhalsar och problem som uppstår i samband med implementering avkorttidsuthyrning samt hur marknadsplattformar kan hjälpa fastighetsägare att lösa dessa.Studien visade att fastighetsägare har börjat använda sig av korttidsuthyrningar i en störreutsträckning än tidigare. Fastighetsägarna var positiva till att använda sig av korttidsuthyrningarsom ett verktyg för att minska vakanser. Det visade sig också att det finns problem medimplementering av korttidsuthyrningar från ett fastighetsägarperspektiv. De största problemensom studien visade på var transparens av tomma lokaler, hur korttidsuthyrningar kan påverkafastighetsvärden negativt samt tidsåtgången för att skriva ett korttidskontrakt. Vissa problemkan lösas av marknadsplattformar för korttidsuthyrning medans andra behöver lösas avfastighetsbranschen i sin helhet.
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Yu, Chunhui. "Managing risk with short term futures contracts." Thesis, [Tuscaloosa, Ala. : University of Alabama Libraries], 2009. http://purl.lib.ua.edu/2138.
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Degerli, Ahmet. "Short-term Industrial Production Forecasting For Turkey." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614689/index.pdf.
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This thesis aims to produce short-term forecasts for the economic activity in Turkey. As a proxy for the economic activity, industrial production index is used. Univariate autoregressive distributed lag (ADL) models, vector autoregressive (VAR) models and combination forecasts method are utilized in a pseudo out-of-sample forecasting framework to obtain one-month ahead forecasts. To evaluate the models&rsquoforecasting performances, the relative root mean square forecast error (RRMSFE) is calculated. Overall, results indicate that combining the VAR models with four endogenous variables yields the most substantial improvement in forecasting performance, relative to benchmark autoregressive (AR) model.
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Cicconi, Claudia. "Essays on macroeconometrics and short-term forecasting." Doctoral thesis, Universite Libre de Bruxelles, 2012. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209660.
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The thesis, entitled "Essays on macroeconometrics and short-term forecasting",is composed of three chapters. The first two chapters are on nowcasting,
a topic that has received an increasing attention both among practitioners and
the academics especially in conjunction and in the aftermath of the 2008-2009
economic crisis. At the heart of the two chapters is the idea of exploiting the
information from data published at a higher frequency for obtaining early estimates
of the macroeconomic variable of interest. The models used to compute
the nowcasts are dynamic models conceived for handling in an efficient way
the characteristics of the data used in a real-time context, like the fact that due to the different frequencies and the non-synchronicity of the releases
the time series have in general missing data at the end of the sample. While
the first chapter uses a small model like a VAR for nowcasting Italian GDP,
the second one makes use of a dynamic factor model, more suitable to handle
medium-large data sets, for providing early estimates of the employment in
the euro area. The third chapter develops a topic only marginally touched
by the second chapter, i.e. the estimation of dynamic factor models on data characterized by block-structures.
The firrst chapter assesses the accuracy of the Italian GDP nowcasts based
on a small information set consisting of GDP itself, the industrial production
index and the Economic Sentiment Indicator. The task is carried out by using
real-time vintages of data in an out-of-sample exercise over rolling windows
of data. Beside using real-time data, the real-time setting of the exercise is
also guaranteed by updating the nowcasts according to the historical release calendar. The model used to compute the nowcasts is a mixed-frequency Vector
Autoregressive (VAR) model, cast in state-space form and estimated by
maximum likelihood. The results show that the model can provide quite accurate
early estimates of the Italian GDP growth rates not only with respect
to a naive benchmark but also with respect to a bridge model based on the
same information set and a mixed-frequency VAR with only GDP and the industrial production index.
The chapter also analyzes with some attention the role of the Economic Sentiment
Indicator, and of soft information in general. The comparison of our
mixed-frequency VAR with one with only GDP and the industrial production
index clearly shows that using soft information helps obtaining more accurate
early estimates. Evidence is also found that the advantage from using soft
information goes beyond its timeliness.
In the second chapter we focus on nowcasting the quarterly national account
employment of the euro area making use of both country-specific and
area wide information. The relevance of anticipating Eurostat estimates of
employment rests on the fact that, despite it represents an important macroeconomic
variable, euro area employment is measured at a relatively low frequency
(quarterly) and published with a considerable delay (approximately
two months and a half). Obtaining an early estimate of this variable is possible
thanks to the fact that several Member States publish employment data and
employment-related statistics in advance with respect to the Eurostat release
of the euro area employment. Data availability represents, nevertheless, a
major limit as country-level time series are in general non homogeneous, have
different starting periods and, in some cases, are very short. We construct a
data set of monthly and quarterly time series consisting of both aggregate and
country-level data on Quarterly National Account employment, employment
expectations from business surveys and Labour Force Survey employment and
unemployment. In order to perform a real time out-of-sample exercise simulating
the (pseudo) real-time availability of the data, we construct an artificial
calendar of data releases based on the effective calendar observed during the first quarter of 2012. The model used to compute the nowcasts is a dynamic
factor model allowing for mixed-frequency data, missing data at the beginning
of the sample and ragged edges typical of non synchronous data releases. Our
results show that using country-specific information as soon as it is available
allows to obtain reasonably accurate estimates of the employment of the euro
area about fifteen days before the end of the quarter.
We also look at the nowcasts of employment of the four largest Member
States. We find that (with the exception of France) augmenting the dynamic
factor model with country-specific factors provides better results than those
obtained with the model without country-specific factors.
The third chapter of the thesis deals with dynamic factor models on data
characterized by local cross-correlation due to the presence of block-structures.
The latter is modeled by introducing block-specific factors, i.e. factors that
are specific to blocks of time series. We propose an algorithm to estimate the model by (quasi) maximum likelihood and use it to run Monte Carlo
simulations to evaluate the effects of modeling or not the block-structure on
the estimates of common factors. We find two main results: first, that in finite samples modeling the block-structure, beside being interesting per se, can help
reducing the model miss-specification and getting more accurate estimates
of the common factors; second, that imposing a wrong block-structure or
imposing a block-structure when it is not present does not have negative
effects on the estimates of the common factors. These two results allow us
to conclude that it is always recommendable to model the block-structure
especially if the characteristics of the data suggest that there is one.
Doctorat en Sciences économiques et de gestion
info:eu-repo/semantics/nonPublished
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Huisken, Giovanni. "Inter-urban short-term traffic congestion prediction." Enschede : University of Twente [Host], 2006. http://doc.utwente.nl/57639.
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Bédard, Joël. "Improvement of short-term numerical wind predictions." Mémoire, École de technologie supérieure, 2010. http://espace.etsmtl.ca/296/1/B%C3%A9dard_Jo%C3%ABl.pdf.
Full textAbstract:
Avec la croissance soutenue de l’énergie éolienne sur les marchés énergétiques, les
opérateurs des réseaux électriques ont de plus en plus de défis à relever en matière
d’équilibrage de réseau, le tout afin de minimiser les coûts associés à la gestion des autres
sources énergétiques. Le vent étant une source énergétique variable, la prévision de la
puissance éolienne est donc l’une des solutions qui permettra à ce type d’énergie de devenir
viable du point de vue économique, tant sur les marchés régulés que dans les marchés
ouverts. Dorénavant, il semble qu’il y ait un besoin urgent pour des modèles permettant de
prédire de manière fiable la puissance éolienne à court-terme (0 – 48 h); ceci, afin de
maintenir l’intégration de l’énergie éolienne dans le portefeuille énergétique des différentes
juridictions.
En fonction des besoins de l’industrie éolienne, « Environnement Canada » effectue, depuis
trois ans, des prévisions météorologiques expérimentales dans l’est canadien à l’aide d’un
modèle de prévisions numériques à aire limitée (GEM-LAM 2.5 km). La région couverte
englobe la péninsule gaspésienne ainsi qu’une partie des provinces maritimes. Cette région
couvre plusieurs sites éoliens tels que North Cape. Ce site est situé à l’Ile du Prince Édouard
où le Wind Energy Institute of Canada opère un centre d’essais éolien. Une analyse
préliminaire des prévisions et une inspection minutieuse de ce site ont permis de démontrer
que, bien que la résolution du modèle soit déjà relativement haute, elle manque tout de même
de raffinement afin de bien représenter les phénomènes météorologiques pour ce site côtier à
topographie complexe. Pour cette raison, un module géophysique de traitement statistique
des sorties (Geophysic Model Output Statistic (GMOS)) a été développé et appliqué afin de
permettre une optimisation de l’utilisation du modèle de prévision météorologique à des fins
de prévision de la puissance éolienne à court-terme. GMOS diffère des MOS couramment
utilisés dans les centres météorologiques par les aspects suivants : 1) il prend en compte les
paramètres géophysiques régionaux (hauteur topographique, rugosité de surface, etc.) ainsi
que la direction du vent; 2) il peut être directement appliqué pour corriger les sorties de
différents modèles numériques sans entraînement, bien qu’un entraînement soit bénéfique.
Ce module statistique a été entrainé et testé pour le site de North Cape, où il a réduit l’erreur
quadratique des prévisions de 25 à 30 %. Cette amélioration significative est observable
pour tous les horizons temporels ainsi que pour la majorité des conditions météorologiques.
De plus, la signature topographique de l’erreur de prévision a été éliminée suite à
l’application du GMOS. D’ailleurs, le modèle de prévision numérique combiné au GMOS
offre une prévision supérieure à celle de la persistance dès un horizon de 2 h. Ce gain n’était
observable qu’à partir d’un horizon de 4 h sans l’utilisation du GMOS. Enfin, une validation
effectuée pour un site établi à Bouctouche (Nouveau Brunswick), présentant des
améliorations similaires des prévisions de vent de surface, a permis de démontrer
l’applicabilité générale de la méthode.
Cette étude, présentant un module statistique permettant l’optimisation de l’utilisation des
prévisions météorologiques à haute résolution, a aussi contribué au développement d’une
méthodologie afin de mieux comprendre les erreurs de prévisions reliées aux différentes
conditions météorologiques. Cet outil d’analyse a permis d’évaluer la contribution d’erreur
de phase et d’amplitude pour des conditions atmosphériques normales ainsi que pour divers
évènements météorologiques à caractère dynamique tels que les variations subites de vitesse
du vent, le passage de dépressions etc. Une compréhension accrue des erreurs de prévisions
ainsi que l’acquisition de prévisions éoliennes plus précises permettront d’augmenter la
valeur économique de l’énergie éolienne sur le marché.
26
Hall, Debbora. "Memory for rhythm and short-term memory." Thesis, University of York, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.495877.
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Hu, Jun. "Short-term congestion prediction for vehicle navigation." Thesis, Imperial College London, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.535007.
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Dahmen, Johannes C. "Short-Term Plasticity in the Auditory System." Thesis, University of Oxford, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.525284.
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Rindzevičius, Vytautas. "Short-term effects of controlled conservation burning." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-234965.
Full textAbstract:
In this study, the immediate and short term (three months) effects of conservation burning have been investigated in coniferous forests in southeastern Sweden. Five tree species were investigated Picea abies (Norway spruce), Pinus sylvestris (Scots pine), Populus tremula (aspen), Betula pendula (silver birch) and Betula pubescens (downy birch), as well as ground vegetation of mosses, dwarf shrubs and ground lichens. Burning increased the proportion of live deciduous tree shoots from 51 % to 81 % and the live tree shoot size distribution of four tree species was significantly changed by fire. Fire affected the tree species differently. Three months after burning deciduous tree species exhibited strong sprouting, while P. sylvestris had established many seedlings, significantly increasing its share of the tree stand. P. abies lacked any visible positive response to burning and its number of live shoots decreased by 83 %. Mineral soil was exposed on only the moss vegetation and covered just 4 % of the studied plot area. The initial vegetation response to fire was negative, but significant dwarf shrub recovery was detected three months after burning.
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Elkins, Ronald D. "Short-term planning and forecasting for petroleum." Thesis, Monterey, California. Naval Postgraduate School, 1988. http://hdl.handle.net/10945/23389.
Full textAbstract:
The Defense Fuel Supply Center (DFSC) has, in recent past, been unable to adequately forecast for short-term petroleum requirements. This has resulted in inaccurate replenishment quantities and required short notice corrections which interrupted planned resupply methods. The relationship between the annual CINCLANTFLT DFM budget and sales from the the Norfolk Defense Fuel Support Point (DFSP) is developed and the past sales data from the Norfolk DFSP is used to construct seasonality indices. Finally, the budget/sales relationship is combined with the seasonality indices to provide a new forecasting model. This model is then compared with the current one for FY-88 monthly forecasts. The comparison suggests that the new model can provide accurate, timely requirements data and improve resupply of the Norfolk Defense Fuel Support Point. Keywords: Petroleum, Forecasting, Seasonality, Logistics, Inventory management. (JES)
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Gilburt, Simon John Arthur. "Psychopharmacological aspects of short-term information processing." Thesis, University of Leeds, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.277353.
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Brennan, Richard John. "Novel short-term tests for environmental carcinogens." Thesis, University of Warwick, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.357499.
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Thorn, Annabel S. C. "Language specialisation in verbal short-term memory." Thesis, University of Bristol, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266906.
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Mikan, Kathrin Angela Maria. "Verbal short-term memory and vocabulary learning." Thesis, University of Sussex, 2013. http://sro.sussex.ac.uk/id/eprint/44799/.
Full textAbstract:
This thesis addressed two key issues. The first was the extent to which verbal short-term memory (STM) for item and order information can be differentiated in terms of their underlying neural mechanisms. The second was to analyze the relative contributions of item and order STM to vocabulary learning in bilingual (BL) and monolingual (ML) children and ML adults. The first issue was addressed with four studies. Three used electroencephalography (EEG) with ML adults, BL adults and ML children. The aim was to determine whether there is any evidence that the two types of verbal STM have different neural signatures. The fourth study used transcranial magnetic stimulation (TMS) in ML adults to test the hypothesis that the right intraparietal sulcus (IPS) is involved in order STM but not item STM. The second issue was addressed by two behavioural studies. The first was a large-scale longitudinal study testing item and order STM in relation to natural vocabulary acquisition in 7 to 10 year old BL and ML children. The children were tested once in the beginning and once in the end of the school year. In addition, ML children learning a second language were examined in the end of the school year. The second behavioural study explored therelationship of item and order STM with new-word-learning in ML adults using artificially-created nonwords. Some evidence was found to support the view that the distinction of item and order STM is a useful one. Results of the EEG data suggested differences in patterns of neuro-electrical activity for ML and BL adults and ML children when they are performing item STM and order STM tasks. The results suggest that order STM is important for new word learning in one´s native language learning, where there has already been some exposure to this language, but not in complete novice language learners.
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Santos, Gustavo Sato dos. "Towards short-term forecasting of ventricular tachyarrhythmias." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/41620.
Full textAbstract:
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 48-49).
This thesis reports the discovery of spectral patterns in ECG signals that exhibit a temporal behavior correlated with an approaching Ventricular Tachyarrhythmic (VTA) event. A computer experiment is performed where a supervised learning algorithm models the ECG signals with the targeted behavior, applies the models on other signals, and analyzes consistencies in the results. The procedure was successful in discovering patterns that happen before the onset of a VTA in 23 of the 79 ECG signal segments examined. A database with signals from healthy patients was used as a control, and there were no false positives on this database. The patterns discovered by this modeling process, although promising, still require thorough external validation. An important contribution of this work is the experimental procedure itself, which can be easily reproduced and expanded to search for more complicated patterns.
by Gustavo Sato dos Santos.
M.Eng.
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Allcroft, David John. "Statistical models for short-term animal behaviour." Thesis, University of Edinburgh, 2001. http://hdl.handle.net/1842/11132.
Full textAbstract:
This thesis aims to identify appropriate methods for the modelling of animal behaviour data, and in the wider context, any time series of categorical data. We make extensive use of a large dataset of cow feeding behaviour, consisting of full feeding records for a number of cows over one month, the data taking the form of binary time series, i.e. feeding/non-feeding periods. After initial exploratory data analysis, we go on to investigate three classes of model: latent Gaussian, hidden Markov and semi-Markov. The latent Gaussian model assumes the binary data occur from the thresholding of an underlying continuous variable. We identify the one-to-one relationship between the autocorrelation of the observed and latent variables and consider techniques for parameter estimation. For a multivariate stationary Gaussian process we show the asymptotic equivalence of the likelihood written in its spectral and conventional forms, and provide a proof that for short-term memory processes such as ARMA models, a good approximation for the spectral form is obtained using Fourier transforms of correlations at only the first few lags. A simulation study highlights the saving in computing time that this offers, and also shows that, in contrast to the least squares methods considered, the number of lags to retain is not crucial for obtaining efficient parameter estimates. Hidden Markov models also directly model the underlying state of the animal, but the latent variable here is discrete and follows a Markov chain, observations being dependent only on the current state. However, this type of model constrains the durations between feeding events to follow a mixture of geometric distributions, which is seen to be inappropriate for the data considered. Semi-Markov models simply involve the animal moving between a set of feeding and non-feeding states according to a set of transition probabilities, the marginal distributions for durations in each state being specified directly.
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Nigrini, L. B., and G. D. Jordaan. "Short term load forecasting using neural networks." Journal for New Generation Sciences, Vol 11, Issue 3: Central University of Technology, Free State, Bloemfontein, 2013. http://hdl.handle.net/11462/646.
Full textAbstract:
Published ArticleSeveral forecasting models are available for research in predicting the shape of electric load curves. The development of Artificial Intelligence (AI), especially Artificial Neural Networks (ANN), can be applied to model short term load forecasting. Because of their input-output mapping ability, ANN's are well-suited for load forecasting applications. ANN's have been used extensively as time series predictors; these can include feed-forward networks that make use of a sliding window over the input data sequence. Using a combination of a time series and a neural network prediction method, the past events of the load data can be explored and used to train a neural network to predict the next load point. In this study, an investigation into the use of ANN's for short term load forecasting for Bloemfontein, Free State has been conducted with the MATLAB Neural Network Toolbox where ANN capabilities in load forecasting, with the use of only load history as input values, are demonstrated.
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Leon, Ojeda Luis. "Short-term multi-step ahead traffic forecasting." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENT081/document.
Full textAbstract:
Dans le cadre des systèmes de transport intelligents (ITS), cette thèse concerne la conception d'une méthodologie de prédiction, en temps réel et pour différents horizons, du temps de parcours à partir des données de vitesse et de débit d'une route instrumentée. Pour atteindre cet objectif, deux approches sont considérées dans cette thèse. La première approche, dite « sans modèle », utilise exclusivement des mesures de vitesse. Grâce à l'utilisation astucieuse des données historiques, nous avons résolu le problème de prédiction comme étant un problème de filtrage. Pour ce faire, des données historiques sont utilisées pour construire des pseudo-observations qui alimentent un filtre de Kalman adaptatif (AKF). Sous une hypothèse de Gaussianité, les statistiques du bruit de processus sont estimées en temps-réel, tandis que les statistiques du pseudo-bruit d'observation sont déduites des données historiques adéquatement classées. La seconde approche, dite ‘'basée-modèle'', utilise principalement des mesures de débit et de vitesse. Contrairement à la précédente approche où la résolution spatiale est fixée par l'emplacement des capteurs, une discrétisation spatiale plus fine est considérée. Celle-ci s'avère possible grâce à l'utilisation du modèle CTM (Cell Transmission Model). Un observateur d'état commuté, de type Luenberger, permet d'estimer les états internes (densités des cellules). En utilisant uniquement les prédictions des débits des conditions frontières via une approche de type AKF similaire à celle développée dans la première approche, le modèle CTM contraint permet de prédire les densités des cellules et d'en déduire les vitesses et le temps de parcours. Les méthodes développées ont été validées expérimentalement en considérant la rocade sud grenobloise comme cas d'étude. Les résultats montrent que les deux méthodes présentent de bonnes performances de prédiction. Les méthodes proposées performent mieux que celles basées sur une utilisation directe des moyennes historiques. Pour l'ensemble des données considérées, l'étude a également montré que l'approche ‘'basée modèle‘' est plus adaptée pour des horizons de prédictions de moins de 30 minThis dissertation falls within the domain of the Intelligent Transportation Systems (ITS). In particular, it is concerned with the design of a methodology for the real-time multi-step ahead travel time forecasting using flow and speed measurements from a instrumented freeway. To achieve this objective this thesis develops two main methodologies. The first one, a model-free, uses only speed measurements collected from the freeway, where a mean speed is assumed between two consecutive collection points. The travel time is forecasted using a noise Adaptive Kalman Filter (AKF) approach. The process noise statistics are computed using an online unbiased estimator, while the observations and their noise statistics are computed using the clustered historical traffic data. Forecasting problems are reformulated as filtering ones through the use of pseudo-observations built from historical data. The second one, a model-based, uses mainly traffic flow measurements. Its main appealing is the use of a mathematical model in order to reconstruct the internal state (density) in small road portions, and consequently exploits the relation between density and speed to forecast the travel time. The methodology uses only boundary conditions as inputs to a switched Luenberger state observer, based on the ``Cell Transmission Model'' (CTM), to estimate the road initial states. The boundary conditions are then forecasted using the AKF developed above. Consequently, the CTM model is run using the initial conditions and the forecasted boundaries in order to obtain the future evolution of densities, speeds, and finally travel time. The added innovation in this approach is the space discretization achieved: indeed, portions of the road, called ``cells'', can be chosen as small as desired and thus allow obtaining a finer tracking of speed variations. In order to validate experimentally the developed methodologies, this thesis uses as study case the Grenoble South Ring. This freeway, enclosing the southern part of the city from A41 to A480, consists of two carriageways with two lanes. For this study only the direction east-west was considered. With a length of about 10.5 km, this direction has 10 on-ramps, 7 off-ramps, and is monitored through the Grenoble Traffic Lab (GTL) that is able to provide reliable traffic data every 15 s, which makes it possible for the forecasting strategies to be validated in real-time. The results show that both methods present strong capabilities for travel time forecasting: considering the entire freeway, in 90% of the cases it was obtained a maximum forecasting error of 25% up to a forecasting horizon of 45 min. Furthermore, both methods perform as good as, or better than, the average historical. In particular, it is obtained that for horizons larger than 45 min, the forecasting depended exclusively on the historical data. For the dataset considered, the assessment study also showed that the model-based approach was more suitable for horizons shorter than 30 min
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Jay, Oliver Edward. "Short-term fingertip contact with cold materials." Thesis, Loughborough University, 2002. https://dspace.lboro.ac.uk/2134/33785.
Full textAbstract:
Typically, industry workers are exposed to, and may touch, either accidentally or intentionally, many surfaces of different materials (e g machine parts, walls etc.) For environments containing hot surfaces, standards are available to determine the temperature limits for these surfaces in order to minimise safety risks (skin bums, EN 563 1994). However, no such standard is available for cold surfaces and for those working in such a cold environment, accidental skin contact exposure and the resultant skin cooling could pose a health and safety risk in terms of discomfort, pain, numbness and skin damage Data was collected for the derivation of a cold surfaces safety standard (European Union project SMT4-CT97-2149), providing a relation between material type, surface temperature and risk of pain and frostbite for the index fingertip of the non-dominant hand, the overall aim being to use the data to develop a predictive model of fingertip contact cooling allowing the prediction for various materials, temperatures and body thermal states within and outside the actual tested ranges.
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Garisch, Jarryd. "Short-term return reversion on the JSE." Master's thesis, University of Cape Town, 2013. http://hdl.handle.net/11427/12331.
Full textAbstract:
Includes abstract.This study explores the existence of mean reversion in returns on the Johannesburg Stock Exchange (JSE). Finding that most research on the JSE applies to the long term, this paper investigates mean reversion across relatively shorter periods. Thus investment horizons between 1 and 30 days are considered. This paper finds that the standard short-term reversal strategy can be improved upon by a double application of the strategy. Furthermore, return reversal are found to be strongest when comparing prior 5 day returns with future 5 day returns. The best strategy is found to be the double application of the standard short-term reversal strategy using the 10th percentile of the 5 day prior returns and the 10th percentile of the 10 day prior returns. The long positions of this strategy still generated attractive returns over the market crash of 2008, making this a robust strategy. In general, long strategies outperform short strategies. However, over the crash period of 1 August 2008 to 1 April 2009 the short strategies offered more attractive returns and higher information ratios. Other additions to the strategy, such as moving average and kicker rules, fail to add value or reduce risk. Extending the holding period of the standard short-term reversal strategy generally results in poorer performance across all percentiles. The results in this paper pertain to the top 60 shares on the Johannesburg Stock Exchange ranked by market capitalisation on 10 August 2012. These cover a sample period ranging from 1 January 1998 to 10 August 2012. The analysis presented in this paper does not factor in the influence of trading costs. Such costs may be significant when portfolios are closed and opened frequently. An additional caveat is that many strategies lead to a small average number of positions, which is problematic for institutional traders.
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Voráček, Lukáš. "Quantitative approach to short-term financial planning." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-113571.
Full textAbstract:
The aim of this study is to certify the legitimacy of employing quantitative methods in the day-to-day business practice. The task is approached as a case study of a real-life financial planning process. I work with the financial data of POS Media Czech Republic (a media company providing point-of-sale advertising solutions). My intention is to simulate the projection of a pro forma income statement with the use of quantitative methods. More specifically, I am applying time series prediction techniques in order to forecast POS Media's sales. The goal is, first, to demonstrate that quantitative techniques can be handled even with limited statistical background and, second, to discuss the relevancy of the obtained results. In the methodical part of my thesis I deal with the theoretical aspects of financial planning. I further describe various methods of sales forecasting (qualitative vs. quantitative). Special emphasis is put on time series prediction methods. In the application part I provide a short description of POS Media and its business. I use time series decomposition techniques to predict POS Media's sales in 2012. Consequently, I outline the rest of the pro forma income statement.
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Jones, Erle Baxter 1953. "Short-term variation during asbestos abatement activities." Thesis, The University of Arizona, 1987. http://hdl.handle.net/10150/276531.
Full textAbstract:
The fibrous aerosol monitor (FAM) was designed to count fibrous particulates as accurately as the standard method, P & CAM 239, now NIOSH 7400. The Hi-Vol (HV) method, a modification of the standard method, was developed to collect fibers over a shorter time interval (i.e., 10-minutes) with the same accuracy as the standard method. The current study sought to compare the HV method with the FAM to assess its validity in measuring airborne asbestos levels and to assess the importance of short-term variation in asbestos levels in determining appropriate respiratory protection. Correlation between the FAM and HV showed a poor linear relationship in all comparison studies. However, there was good correlation between the average of short-term HV samples and long-term time-weighted average (TWA) samples at reported low levels of airborne asbestos. All membrane filter techniques showed strong correlation with each other, but were weakly correlated with the FAM. (Abstract shortened with permission of author.)
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Dogan, Gamze. "Grid reliability assessment for short-term planning." Doctoral thesis, Universite Libre de Bruxelles, 2018. https://dipot.ulb.ac.be/dspace/bitstream/2013/276775/3/Content.docx.
Full textAbstract:
With the increasing amount of renewable and difficult-to-forecast generation units, Transmission System Operators (TSO) face new challenges to operate the grid properly. The deterministic N-1 criterion is currently used to assess grid reliability. This criterion states that the loss of an active component should not trigger the violation of operational constraints. It has been chosen in the conventional context of electricity in which large units produced power transmitted to the consumer through the transmission and the distribution systems. The renewable energy sources, the distributed generations, and the liberalization of the electricity market led to a revolution in power systems. Renewable energies present intrinsic variability and limited predictability. Those variables are thus subject to forecasting errors. Distributed generations changed the structure of the power system to include smaller productions dispersed in the grid. The competitive electricity market led the consumers to react to electricity prices. The load is thus now subject to higher forecasting errors. An increasing share of the power system’s variables is thus now subject to errors that are likely to affect the operations and the planning of the grid. The N-1 criterion reaches limitations in considering the new characteristics of the power system. To account for this evolution, TSOs have to make a shift in paradigm. They must go from the N-1 criterion to a reliability-based approach, with risk management and integration of errors on forecasted values. This amounts to going from deterministic to probabilistic approaches capable of quantifying this risk.The purpose of this research project is to develop the basis of an industrial tool. The method considers thus the barriers to the use of a probabilistic method for grid planning. TSOs are indeed reluctant to give up the N-1 criterion. They fear that a probabilistic method would be too difficult to understand and apply and that the related computational time would be too long for the operational planning.The method proposed in this research project aims at overcoming those barriers. The method sets the basis of a decision support tool for the planners to make sound decisions. It is thus not a black-box and the planners are included in the assessment. The method is based on the current work of the planners and widens it to englobe probabilistic considerations. It offers thus a smooth evolution from a deterministic to a probabilistic method which will ease the industrial development of the tool using it. The method is called Discrete Forecast ERrors Scenarios method: DIFERS. It has been developed to be consistent with the operational planning in terms of time constraints and available information. It relies on three evolutions from the deterministic N-1 criterion: 1. Include possible variations from the best estimate of the forecasts.2. Enlarge the contingency list to higher N-k events.3. Consider the impact and the probability of the events to compute their risk.The contingency list evolves thus toward a risk-based classification of events. The planners’ work aims then at proposing actions to decrease the risk to an acceptable level. The first step of DIFERS is performed off-line to relax the time constraints. It aims at evaluating the contingency list for a set of situations. It performs an assessment on the most probable events, considering a larger group than the N-1 criterion. The assessment focuses on N-1 and nearby N-2 events. The nearby events have been selected based on a distance criterion defined in terms of number of components in the smallest path from one component to another. Some random N-3 and N-4 events are also analyzed to assess the evolution of the risk with regard to the number of failing components. Continuous variables are represented by their probability density functions (PDFs), which represent the variation range for the set of situations considered. Those PDFs are discretized to limit the computational time. The assessment of the contingencies is performed on each combination of those discrete points. The second step uses the contingency list developed in step 1 to assess the risk related to a specific situation: a grid plan. The PDFs used in this step represent the forecasting errors on the continuous variables for the grid plan considered. They are also discretized and each combination is tested with the events of the contingency list. At the end of the assessment, indicators are computed and provided to the planner. The planner can then propose actions to be tested by the tool to see their impact on the reliability indicators. The assessment stops once the reliability target is met.The final step aims at updating the information computed in step 2 with newly acquired forecasts. As real-time is closer, those forecasts are more reliable. The method has been tested on a plausible scenario and on a simplified version of the Belgian grid. The load and the offshore wind production have been considered as input variables for this implementations. The results show that there is an interest in evolving toward a risk-based assessment to capture the new characteristics of the evolving context of electricity supply. The implementation of the DIFERS method should continue on several scenarios. It should integrate all continuous variables such as solar and onshore productions. Moreover, all real-life considerations on the input variables, such as correlations, should be included to represent the power system as best as possible.This research project has been conducted in collaboration with the Belgian TSO Elia and it has been financed by the Doctiris grant of Innoviris.Doctorat en Sciences de l'ingénieur et technologie
info:eu-repo/semantics/nonPublished
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Söderberg, Max Joel, and Axel Meurling. "Feature selection in short-term load forecasting." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259692.
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This paper investigates correlation between energy consumption 24 hours ahead and features used for predicting energy consumption. The features originate from three categories: weather, time and previous energy. The correlations are calculated using Pearson correlation and mutual information. This resulted in the highest correlated features being those representing previous energy consumption, followed by temperature and month. Two identical feature sets containing all attributes1 were obtained by ranking the features according to correlation. Three feature sets were created manually. The first set contained seven attributes representing previous energy consumption over the course of seven days prior to the day of prediction. The second set consisted of weather and time attributes. The third set consisted of all attributes from the first and second set. These sets were then compared on different machine learning models. It was found the set containing all attributes and the set containing previous energy attributes yielded the best performance for each machine learning model. 1In this report, the words ”attribute” and ”feature” are used interchangeably.I denna rapport undersöks korrelation och betydelsen av olika attribut för att förutspå energiförbrukning 24 timmar framåt. Attributen härstammar från tre kategorier: väder, tid och tidigare energiförbrukning. Korrelationerna tas fram genom att utföra Pearson Correlation och Mutual Information. Detta resulterade i att de högst korrelerade attributen var de som representerar tidigare energiförbrukning, följt av temperatur och månad. Två identiska attributmängder erhölls genom att ranka attributen över korrelation. Tre attributmängder skapades manuellt. Den första mängden innehåll sju attribut som representerade tidigare energiförbrukning, en för varje dag, sju dagar innan datumet för prognosen av energiförbrukning. Den andra mängden bestod av väderoch tidsattribut. Den tredje mängden bestod av alla attribut från den första och andra mängden. Dessa mängder jämfördes sedan med hjälp av olika maskininlärningsmodeller. Resultaten visade att mängden med alla attribut och den med tidigare energiförbrukning gav bäst resultat för samtliga modeller.
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HUANG, JIAN-KAI, and 黃建凱. "Short-Term Electric Load Forecasting Model Using Long Short-Term Memory." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/3wr7cn.
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碩士逢甲大學
電機工程學系
107
The smart grid is considered to be a highly complex system, and its effective management is a huge challenge. Load forecasting is closely related to the development of power systems, such as energy market analysis, economic dispatch and safety assessment, and has therefore been identified as a key issue in how to effectively manage the grid. How to effectively use the vast amount of information provided by smart meters will be the focus of future research. This paper proposes three short-term load forecasting architectures based on Long short-term memory neural networks (LSTM). There are several important improvements to improve forecasting performance. First, to improve the accuracy of neural networks, an algorithm combining wavelet transform and LSTM is proposed. Second, using the autocorrelation coefficient to filter the input data to enhance the value of the data, it can improve the efficiency of machine learning. And combined with different features to improve the overall architecture versatility. In addition, a time-series data segmentation architecture is proposed. For time-series data, data segmentation is performed under different conditions. This can effectively improve the performance of a single LSTM. The amount of data that LSTM needs to process is reduced. If it is combined with parallel computing technology, the required computing time can be greatly reduced. Finally, a time-series multi-step target prediction method is proposed, and the accuracy can still be maintained under the condition of prolonging the predicted target distance time. This study also designed a graphical user interface (GUI) for short-term load forecasting, so that users can get the information quickly and easily.
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Lee, Meng-Hsuan, and 李孟軒. "Short-term Load Forecasting with Clustering and Long-Short Term Memory Model." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/3q54gw.
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碩士國立中山大學
應用數學系研究所
107
This study discusses the effects of cluster analysis methods (K-medoids) and long-short term memory (LSTM) neural network models on short-term load electricity forecasts.We use the historical load data, as well as the actual and predicted temperatures from 2015 to 2018 provided by the Central Weather Service to build forecasting model for future load prediction. First, we apply cluster analysis by grouping the power and temperature data, combining the periodic basis function as the input variable of the model used by the Recurrent Neural Network (RNN) of Jiang (2018). Second, to improve the predictive power of the RNN, we apply the results of the cluster analysis, and later utilize the LSTM model with longer time steps. As for the evaluation criterion, the model performance is examined by the mean absolute percentage error (MAPE) between the predicted result and the true load. At the end, the MAPE results for the daily load forecast in 2018 are presented and compared with previous results based on recurrent neural network. It is observed that the LSTM has a better performance and we also present the forecasting performance for the first five months of 2019.
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Chen, Chien-Hung, and 陳建宏. "Short-Term Interest Forecasting." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/14917380315502711491.
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碩士淡江大學
財務金融學系碩士在職專班
92
This research is majority adopted time series econometric model as a forecasting approach. We try to find a reasonable and efficient model for predicting Taiwan’s short-term interest rate. Through the research process, we compare with GARCH, Markov Switching and Constant Intensity Jump Model to identify the best performance econometric model. The result indicates that Constant Intensity Jump Model would be the best by the three kind of measurement tool (MAD, RMSE and MAPE). Conclusion, base on basic GARCH Model, and considering the factor of structure change and jump, Constant Intensity Jump Model is the best econometric model to forecast the Taiwan’s short-term interest rate.
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WU, XIAN-CAI, and 吳賢財. "Short-term load forecasting." Thesis, 1991. http://ndltd.ncl.edu.tw/handle/33477606622790175959.
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LI, YONG-SHENG, and 李勇昇. "SHORT-TERM GENERATION RELIABILITY." Thesis, 1988. http://ndltd.ncl.edu.tw/handle/68887988934739525482.
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WeiCheo, Zi, and 周梓為. "Fuzzy System Based Short-term and Very Short-term Solar PV Output Forecasting." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/32115543804948490395.
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碩士國立成功大學
電機工程學系
104
To enhance the accuracy of the photovoltaic (PV) power output forecasting model for energy management system (EMS), this thesis proposes a one-day ahead short-term and real-time very short-term solar PV output forecasting model based on easier accessible information to solve some problems in practical application. The one-day ahead short-term PV output forecast of the proposed forecasting model predicts the PV power output every 15 minutes by using self-organizing map (SOM) and fuzzy inference method. The real-time very short-term PV output forecast of the proposed model constantly tunes the short-term predicted values achieved one-day ahead, once the actual power output one time-step of 15 minutes before is available. Further, from the forecast horizontal solar radiation, a method is proposed to estimate the actual radiation on the surface of the PV panels to have better forecasting accuracy of PV power generation. The proposed method has been tested in a practical 3 kW PV system in Shulin, Taiwan and a 499 kW commercial grid-connected PV system in Tainan, Taiwan. The average short-term forecast error is 4.98% with the average forecast error of 2.67% for real-time very short-term forecast model.