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Dissertations / Theses on the topic 'Forecasting of the state of systems'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 July 2025

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1

Li, Ying. "Forecasting Long Term Highway Staffing Requirements for State Transportation Agencies." UKnowledge, 2016. http://uknowledge.uky.edu/ce_etds/42.

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The transportation system is vital to the nation’s economic growth and stability, as it provides mobility for commuters while supporting the United States’ ability to compete in an increasingly competitive global economy. State Transportation Agencies across the country continue to face many challenges to repair and enhance highway infrastructure to meet the rapid increasing transportation needs. One of these challenges is maintaining an adequate and efficient agency staff. In order to effectively plan for future staffing levels, State Transportation Agencies need a method for forecasting long

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2

Quinn, Niall. "Forecasting of ocean state in a complex estuarine environment : the Solent-Southampton Water Estuarine System." Thesis, University of Southampton, 2012. https://eprints.soton.ac.uk/359671/.

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Coastal flooding is a natural hazard causing devastation to many regions throughout the world, induced by the coincidence of high spring tides, large storm surges and waves. To reduce the risk posed by coastal inundation, warning systems have been developed to enable preparations to an expected threat. Although current operational predictions provide invaluable warnings, uncertainty in model formulations and input datasets, can lead to errors in forecasts. In order to provide coastal managers with the best possible information with which to make decisions, recent research has begun to focus on

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3

Steed, Chad A. "Development of a geovisual analytics environment using parallel coordinates with applications to tropical cyclone trend analysis." Diss., Mississippi State : Mississippi State University, 2008. http://library.msstate.edu/etd/show.asp?etd=etd-10252008-080937.

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4

Shafiei, Mehdi. "Distribution network state estimation, time dependency and fault detection." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/124659/2/Mehdi_Shafiei_Thesis.pdf.

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In this research work, the combination of three novel approaches is established to estimate the states of three-phase balanced and unbalanced distribution networks and using the developed methods for high impedance fault detection. The effectiveness of the developed methods are proposing a fast real-time state estimator with a low number of measurement devices, avoiding bad data detection in state estimation, and dynamically updating fault current thresholds to detect high impedance faults in the distribution networks.

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5

Mansoor, Shaheer. "System Surveillance." Thesis, Linköpings universitet, Statistik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-98189.

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In recent years, trade activity in stock markets has increased substantially. This is mainly attributed to the development of powerful computers and intranets connecting traders to markets across the globe. The trades have to be carried out almost instantaneously and the systems in place that handle trades are burdened with millions of transactions a day, several thousand a minute. With increasing transactions the time to execute a single trade increases, and this can be seen as an impact on the performance. There is a need to model the performance of these systems and provide forecasts to giv

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6

Paramygin, Vladimir A. "Towards a real-time 24/7 storm surge, inundation and 3-D baroclinic circulation forecasting system for the state of Florida." [Gainesville, Fla.] : University of Florida, 2009. http://purl.fcla.edu/fcla/etd/UFE0024729.

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7

Chou, Shuo-Ju. "A conceptual methodology for assessing acquisition requirements robustness against technology uncertainties." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/39467.

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The lack of system capability, budget, and schedule robustness against technology performance and development uncertainties has led to major setbacks in recent acquisition programs. This lack of robustness stems from the fact that immature technologies have uncertainties in their expected performance and development times and costs that translate to variations in system effectiveness and program development budget and schedule requirements. As such, the objective of this thesis is to formulate an assessment process that better informs acquisition decision-makers of program requirements robus

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8

Lewe, Jung-Ho. "An Integrated Decision-Making Framework for Transportation Architectures: Application to Aviation Systems Design." Diss., Available online, Georgia Institute of Technology, 2005, 2005. http://etd.gatech.edu/theses/available/etd-04132005-204114/unrestricted/Jung-Ho%5FLewe%5F200505%5Fphd.pdf.

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Thesis (Ph. D.)--Aerospace Engineering, Georgia Institute of Technology, 2005.<br>Amy R. Pritchett, Committee Member ; Moore, Mark D., Committee Member ; Wilhite, Alan, Committee Member ; Schrage, Daniel P., Committee Chair ; Mavris, Dimitri N., Committee Co-Chair ; DeLaurentis, Daniel A., Committee Member. Vita. Includes bibliographical references.

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9

Key, Peter Bernard. "Bayesian forecasting with state space models." Thesis, Royal Holloway, University of London, 1986. http://repository.royalholloway.ac.uk/items/87d86ed9-b2e7-4393-9fef-696f8c0cd147/1/.

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This thesis explores the use of State-Space models in Time Series Analysis and Forecasting, with particular reference to the Dynamic Linear Model (DLM) introduced by Harrison and Stevens. Concepts from Control Theory are employed, especially those of observability, controllability and filtering, together with Bayesian inference and classical forecasting methodology. First, properties of state-space models which depart from the usual Gaussian assumptions are examined, and the predictive consequences of such models are developed. These models can lead to new phenomena, for example it is shown th

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10

Fischer, Ulrike. "Forecasting in Database Systems." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-133281.

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Time series forecasting is a fundamental prerequisite for decision-making processes and crucial in a number of domains such as production planning and energy load balancing. In the past, forecasting was often performed by statistical experts in dedicated software environments outside of current database systems. However, forecasts are increasingly required by non-expert users or have to be computed fully automatically without any human intervention. Furthermore, we can observe an ever increasing data volume and the need for accurate and timely forecasts over large multi-dimensional data sets.

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11

Lawson, Richard. "Adaptive state-space forecasting of gas demand." Thesis, Lancaster University, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.358799.

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12

Каткова, Тетяна Ігорівна. "Моделі і методи оцінки, прогнозування та управління стратегічною діяльністю підприємства в умовах невизначеності". Thesis, НТУ "ХПІ", 2017. http://repository.kpi.kharkov.ua/handle/KhPI-Press/35129.

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Дисертація на здобуття наукового ступеня доктора технічних наук за спеціальністю 05.13.03 – системи та процеси керування – Національний технічний університет "Харківський політехнічний інститут", Харків 2018. Дисертаційну роботу присвячено вирішенню важливої та актуальної проблеми наукового обґрунтування і розробки комплексу моделей і методів оцінки, прогнозування та управління стратегічною діяльністю підприємства в умовах невизначеності. Розроблено моделі та методи оцінки і прогнозування стану об'єктів в умовах невизначеності з великим числом можливих станів і великим числом нечітко заданих

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13

Burden, Lindsay Ivey. "Forecasting earthquake losses in port systems." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43615.

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Ports play a critical role in transportation infrastructure, but are vulnerable to seismic hazards. Downtime and reduced throughput from seismic damage in ports results in significant business interruption losses for port stakeholders. Current risk management practices only focus on the effect of seismic hazards on individual port structures. However, damage and downtime of these structures has a significant impact on the overall port system's ship handling operations and the regional, national, and even international economic impacts that result from extended earthquake-induced disruption

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14

Каткова, Тетяна Ігорівна. "Моделі і методи оцінки, прогнозування та управління стратегічною діяльністю підприємства в умовах невизначеності". Thesis, НТУ "ХПІ", 2018. http://repository.kpi.kharkov.ua/handle/KhPI-Press/35128.

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Дисертація на здобуття наукового ступеня доктора технічних наук за спеціальністю 05.13.03 – системи та процеси керування – Національний технічний університет "Харківський політехнічний інститут", Харків 2018. Дисертаційну роботу присвячено вирішенню важливої та актуальної проблеми наукового обґрунтування і розробки комплексу моделей і методів оцінки, прогнозування та управління стратегічною діяльністю підприємства в умовах невизначеності. Розроблено моделі та методи оцінки і прогнозування стану об'єктів в умовах невизначеності з великим числом можливих станів і великим числом нечітко заданих

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15

AMARAL, MARCELO RUBENS DOS SANTOS DO. "STATE SPACE MODELS: MULTIVARIATE FORMULATION APPLIED TO LOAD FORECASTING." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1996. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8707@1.

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CENTRO DE PESQUISA DE ENERGIA ELÉTRICA<br>Os métodos de análise de séries temporais têm se revelado uma importante ferramenta de apoio à tomada de decisões, com importância crescente em um mundo cada vez mais globalizado. Esse fato pode ser ilustrado, entre muitos outros, através de um convênio firmado entre o CEPEL, o Núcleo de Estatística Computacional da PUC/RJ e a Eletrobrás, para se avaliar a utilidade dessas ferramentas nas etapas do planejamento do setor elétrico brasileiro. A metodologia em Espaço de Estado proporcionou o surgimento de duas importantes classes de modelos de pr

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16

Marshall, Richard Carel. "A state space forecasting approach to commodity futures trading." Diss., The University of Arizona, 1991. http://hdl.handle.net/10150/185667.

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State space forecasting originated in the mid-1970's from engineering models based upon the Kalman filter. To date, the application of state space forecasting to commodity and financial markets has been limited. This study examines a system for trading futures contracts using state space forecasts of commodity futures prices. The system is evaluated for a speculative asset (gold) and a nonspeculative commodity (copper). Price forecasts are developed from multivariate state space models, and the variables considered in the models are those which, according to economic theory, may influence pric

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17

Bae, Kyungcho. "Energy consumption forecasting: Econometric model vs state space model." Diss., The University of Arizona, 1994. http://hdl.handle.net/10150/187010.

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This study examines the forecasting performance of two major multivariate methodologies: econometric modeling and multivariate state space modeling. The same variables are used in both models to facilitate comparison. They are evaluated by both expost and exante accuracy of U.S. energy consumption forecasts. Econometric models are highly simplified and a model selection procedure is applied to the models. Two different formats of multivariate state space models are examined: economic structure and identity structure. Goodrich's algorithm is employed to estimate the state space models. The stat

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18

Muthiah, Sathappan. "Design and Maintenance of Event Forecasting Systems." Diss., Virginia Tech, 2021. http://hdl.handle.net/10919/102866.

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With significant growth in modern forms of communication such as social media and micro- blogs we are able to gain a real-time understanding into events happening in many parts of the world. In addition, these modern forms of communication have helped shed light into the increasing instabilities across the world via the design of anticipatory intelligence systems [45, 43, 20] that can forecast population level events like civil unrest, disease occurrences with reasonable accuracy. Event forecasting systems are generally prone to become outdated (model drift) as they fail to keep-up with consta

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19

Piovani, Duccio. "Analysing and forecasting transitions in complex systems." Thesis, Imperial College London, 2015. http://hdl.handle.net/10044/1/31380.

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We analyse in detail a new approach to the monitoring and forecasting of the onset of transitions in high dimensional complex systems by application to the Tangled Nature model of evolutionary ecology and high dimensional replicator systems with a stochastic element, the Stochastic Replicator model. A high dimensional stability matrix is derived for the mean field approximation to the stochastic dynamics. This allows us to determine the stability spectrum about the observed quasi-stable configurations. From overlap of the instantaneous configuration vector of the full stochastic system with th

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20

Hodges, Duncan David. "Propagation forecasting for EHF and SHF systems." Thesis, University of Bath, 2006. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.436876.

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21

STANCIU, MARIA MADALINA. "Artificial Intelligence-Driven Systems for Financial Forecasting." Doctoral thesis, Università degli Studi di Cagliari, 2022. http://hdl.handle.net/11584/333450.

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In recent years, machine learning algorithms have been successfully employed to leverage the potential of identifying hidden patterns of financial market behavior and, consequently, have become the norm in financial applications. This thesis proposes a statistical arbitrage trading strategy with two key elements: an ensemble of regression algorithms for asset return prediction, followed by a dynamic asset selection. More specifically, the extreme heterogeneity of the ensemble is achieved by ensuring model diversity using state-of-the-art machine learning algorithms, data diversity by using di

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22

Loo, Siew Lan. "Neural networks for financial forecasting." Thesis, University College London (University of London), 1994. http://discovery.ucl.ac.uk/1317942/.

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Neural networks demonstrate great potential for discovering non-linear relationships in time-series and extrapolating from them. Results of forecasting using financial data are particularly good [LapFar87, Schöne90, ChaMeh92]. In contrast, traditional statistical methods are restrictive as they try to express these non-linear relationships as linear models. This thesis investigates the use of the Backpropagation neural model for time-series forecasting. In general, neural forecasting research [Hinton87] can be approached in three ways: research into, the weight space, into the physical represe

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Baldwin, Alexander (Alexander Lee), and Jaesung Shin. "New product forecasting in volatile markets." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/92639.

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Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Engineering Systems Division, 2014.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 47-48).<br>Forecasting demand for limited-life cycle products is essentially projecting an arc trend of demand growth and decline over a relatively short time horizon. When planning for a new limited-life product, many marketing and production decisions depend on accurately predicting the life cycle effects on product demand. For products with stable market shares, forecasting demand over the life cycle b

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Trepte, Kai, and Rajaram Narayanaswamy. "Forecasting consumer products using prediction markets." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/53546.

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Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2009.<br>Includes bibliographical references (leaves 105-106).<br>Prediction Markets hold the promise of improving the forecasting process. Research has shown that Prediction Markets can develop more accurate forecasts than polls or experts. Our research concentrated on analyzing Prediction Markets for business decision-making. We configured a Prediction Market to gather primary data, sent out surveys to gauge participant views and conducted in-depth interviews to explain trader behavior. Our re

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naz, saima. "Forecasting daily maximum temperature of Umeå." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-112404.

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The aim of this study is to get some approach which can help in improving the predictions of daily temperature of Umeå. Weather forecasts are available through various sources nowadays. There are various software and methods available for time series forecasting. Our aim is to investigate the daily maximum temperatures of Umeå, and compare the performance of some methods in forecasting these temperatures. Here we analyse the data of daily maximum temperatures and find the predictions for some local period using methods of autoregressive integrated moving average (ARIMA), exponential smoothing

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Castorina, Giovanni. "Artificial intelligence based hybrid systems for financial forecasting." Thesis, University of the West of England, Bristol, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365146.

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Current research carried out on financial forecasting has highlighted some limitations of classical econometric methods based on the assumption that the investigated time series can be described as stationary stochastic processes with Gaussian probability density functions. Chaotic behaviour, fractal characteristics and non-linear dynamics have been emerging in different aspects of the financial forecasting problem. The objective of this thesis is to take a system level perspective of the financial forecasting problem and to explore a number of approaches to enhance more 'traditional' decision

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Feng, Haitang. "Data management in forecasting systems : optimization and maintenance." Phd thesis, Université Claude Bernard - Lyon I, 2012. http://tel.archives-ouvertes.fr/tel-00997235.

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Forecasting systems are usually based on data warehouses for data strorage, and OLAP tools for historical and predictive data visualization. Aggregated predictive data could be modified. Hence, the research issue can be described as the propagation of an aggregate-based modification in hirarchies and dimensions in a data warehouse enironment. Ther exists a great number of research works on related view maintenance problems. However, to our knowledge, the impact of interactive aggregate modifications on raw data was not investigated. This CIFRE thesis is supported by ANRT and the company Antici

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Hirschman, Edward. "Comprehensive forecasting of software integrity in C3I systems." Master's thesis, Virginia Tech, 1992. http://hdl.handle.net/10919/42019.

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The purpose of this project is to forecast the incidence of failures to be encountered by a software package for C3I systems over and throughout its life cycle. It will be assumed that a data base of software previously developed for C3I systems will be used to forecast the software integrity of a software package under initial development. "Software integrity" is defined as a projection of the stream of failures that will be experienced by the new software. The failure history of the mature C3I systems software will be statistically quantified parametrically and by experimental design techniq

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Niu, Mu. "Supply chain dynamics and forecasting." Thesis, Northumbria University, 2009. http://nrl.northumbria.ac.uk/1606/.

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Nowadays, the global supply chain system needs to respond promptly to changes in customer demand and adapt quickly to advancements in technology. Supply chain management becomes an integral approach which links together producers, distributors and customers in collaborative management of the whole system. The variability in orders or inventories in supply chain systems is generally thought to be caused by exogenous random factors such as uncertainties in customer demand or lead time. Studies have shown, however, that orders or inventories may exhibit significant variability, even if customer d

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Chen, Yu. "FORECASTING WITH MIXED FREQUENCY DATA:MIDAS VERSUS STATE SPACE DYNAMIC FACTOR MODEL : AN APPLICATION TO FORECASTING SWEDISH GDP GROWTH." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-29475.

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Most macroeconomic activity series such as Swedish GDP growth are collected quarterly while an important proportion of time series are recorded at a higher frequency. Thus, policy and business decision makers are often confront with the problems of forecasting and assessing current business and economy state via incomplete statistical data due to publication lags. In this paper, we survey a few general methods and examine different models for mixed frequency issues. We mainly compare mixed data sampling regression (MIDAS) and state space dynamic factor model (SS-DFM) by the comparison experime

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Hassanzadeh, Mohammadtaghi. "A New State Transition Model for Forecasting-Aided State Estimation for the Grid of the Future." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/64407.

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The grid of the future will be more decentralized due to the significant increase in distributed generation, and microgrids. In addition, due to the proliferation of large-scale intermittent wind power, the randomness in power system state will increase to unprecedented levels. This dissertation proposes a new state transition model for power system forecasting-aided state estimation, which aims at capturing the increasing stochastic nature in the states of the grid of the future. The proposed state forecasting model is based on time-series modeling of filtered system states and it takes spati

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Holbrook, Blair Sato. "Point-of-sale demand forecasting." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/104397.

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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2016. In conjunction with the Leaders for Global Operations Program at MIT.<br>Thesis: S.M. in Engineering Systems, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2016. In conjunction with the Leaders for Global Operations Program at MIT.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (page 38).<br>Nike Always Available (AA) is a significant global business unit within Nike that allows retail customers to purchase athletic

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Scott, Paul J. "Minimal dimension state space identification, theory and applications in climate forecasting." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ57193.pdf.

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Unosson, Måns. "A Mixed Frequency Steady-State Bayesian Vector Autoregression: Forecasting the Macroeconomy." Thesis, Uppsala universitet, Statistiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-297406.

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This thesis suggests a Bayesian vector autoregressive (VAR) model which allows for explicit parametrization of the unconditional mean for data measured at different frequencies, without the need to aggregate data to the lowest common frequency. Using a normal prior for the steady-state and a normal-inverse Wishart prior for the dynamics and error covariance, a Gibbs sampler is proposed to sample the posterior distribution. A forecast study is performed using monthly and quarterly data for the US macroeconomy between 1964 and 2008. The proposed model is compared to a steady-state Bayesian VAR m

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Koottatep, Pakawkul, and Jinqian Li. "Promotional forecasting in the grocery retail business." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/36142.

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Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2006.<br>Includes bibliographical references (leaves 84-85).<br>Predicting customer demand in the highly competitive grocery retail business has become extremely difficult, especially for promotional items. The difficulty in promotional forecasting has resulted from numerous internal and external factors that affect the demand patterns. It has also resulted from multiple levels of hierarchy that involve different groups in the organization as well as different methods and systems. Moreover, judg

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Poutiainen, Zacharias. "Short-Term Heat Load Forecasting in District Heating Systems : A Comparative Study of Various Forecasting Methods." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-265670.

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Short term heat load forecasts are vital for optimal production planning and commitment of generation units. The generation utility also bares a balance responsibility toward the electricity market as a result of CHP generation. Sub-optimal load forecasts can lead to high costs relating to unit commitment, fuel usage and balancing costs. This thesis presents the empirical comparison of various models for 24h heat load forecasting. Five methods were investigated including four supervised machine learning algorithms; neural networks, support vector machines, random forests and boosted decision t

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Asimakopoulos, Stavros. "A human-computer interaction perspective on forecasting systems design." Thesis, Lancaster University, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.527179.

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Velazquez, Zapata Juan Alberto. "Evaluation of hydrological ensemble prediction systems for operational forecasting." Thesis, Université Laval, 2010. http://www.theses.ulaval.ca/2010/27792/27792.pdf.

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ZEBULUM, RICARDO SALEM. "NEURAL NETWORKS IN LOAD FORECASTING IN ELECTRIC ENERGY SYSTEMS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1995. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=9514@1.

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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>Esta dissertação investiga a utilização de Redes Neurais Artificiais (RNAs) na área de previsão de carga elétrica. Nesta investigação foram utilizados dados reais de energia relativos ao sistema elétrico brasileiro. O trabalho consiste de quatro partes principais: um estudo sobre o problema de previsão de carga no contexto de sistemas elétricos de potência; o estudo e a modelagem das RNAs para previsão de carga; o desenvolvimento do ambiente de simulação; e o estudo de casos. O estudo sobre o problema de previsão de carga

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Li, Qinyun. "A systems dynamics perspective of forecasting in supply chains." Thesis, Cardiff University, 2014. http://orca.cf.ac.uk/69349/.

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Purpose: To evaluate the impact of forecasting on supply chain via a system dynamics perspective. Method/approach: Techniques from Control Theory (such as block diagram, z-transforms, Fourier transforms, Jury’s Inners approach, and frequency response analysis) and Time Series Analysis are used to investigate the performance of supply chains analytically. Simulation is also used to verify the results. Findings: This thesis provides a new and complete proof to the knowledge that Naïve, simple exponential smoothing, and Holt’s forecasting when used in the Order-Up-To (OUT) policy always produce t

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Velázquez, Zapata Juan Alberto. "Evaluation of hydrological ensemble prediction systems for operational forecasting." Doctoral thesis, Université Laval, 2010. http://hdl.handle.net/20.500.11794/22245.

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La prévision hydrologique consiste à évaluer quelle sera l'évolution du débit au cours des prochains pas de temps. En utilisant les systèmes actuels de prévisions hydrologiques déterministes, il est impossible d'apprécier simplement l'incertitude associée à ce type de prévision, ce que peut nuire à la prise de décisions. La prévision hydrologique d'ensemble (PHE) cherche à étayer cette incertitude en proposant, à chaque pas de temps, une distribution de probabilité, la prévision probabiliste, en place et lieu d'une estimation unique du débit, la prévision déterministe. La PHE offre de nombreux

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Hirschman, Edward. "Comprehensive forecasting of software integrity in C I systems /." This resource online, 1992. http://scholar.lib.vt.edu/theses/available/etd-04122010-083444/.

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Arad, Ron 1973. "Sterilization resource forecasting in the medical devices industry." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/33333.

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Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2005.<br>Includes bibliographical references (leaf 73).<br>Sterilization is an example of a procedure that has been outsourced by medical device companies. Sterilization is required for all medical devices and the process used is based on product type. As demand for medical devices increases, production is ramping up, and the need for additional sterilization capacity increases. The time required to build more sterilization capacity can be between six to nine months, and therefore companies are

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Sayyaddelshad, Saleh. "State estimation of nonlinear systems." Licentiate thesis, Luleå tekniska universitet, Signaler och system, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-25774.

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Observer design for nonlinear systems is a popular problem in control theory that has beenstudied from many angles. Since the system state variables, in general, are not available, stateestimation is essential in many control applications, which is why the problem is so attractivefor researchers. One example of a process that has nonlinear dynamics is wood drying.In the wood drying process, there are some unmeasurable variables such as the moisturecontent at the surface and inside the wood, which are important for controlling the drying processfor the purpose of minimizing the energy consumpti

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Hansen, James A. "Adaptive observations in spatially-extended nonlinear dynamical systems." Thesis, University of Oxford, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.284504.

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Pasquali, Flavia. "State space models for the analysis and forecasting of climatic time series." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23081/.

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We analyse climatic time series with state space models in order to compute the forecast distribution. The task is challenging since the temperature series are characterised by large temporal and cross-sectional dimensions. We modify and apply the three-step method proposed in Li et al. Journal of Econometrics 2020, which exploit the cross information in order to improve prediction. We fit the linear Gaussian state space model to different univariate time series, estimating the model parameters with the Kalman filter and computing the prediction errors. The prediction error time series are t

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Tang, Fan. "Structural time series clustering, modeling, and forecasting in the state-space framework." Diss., University of Iowa, 2015. https://ir.uiowa.edu/etd/6002.

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This manuscript consists of two papers that formulate novel methodologies pertaining to time series analysis in the state-space framework. In Chapter 1, we introduce an innovative time series forecasting procedure that relies on model-based clustering and model averaging. The clustering algorithm employs a state-space model comprised of three latent structures: a long-term trend component; a seasonal component, to capture recurring global patterns; and an anomaly component, to reflect local perturbations. A two-step clustering algorithm is applied to identify series that are both globally and

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Jessen, Andreas, and Carina Kellner. "Forecasting Management." Thesis, University of Kalmar, Baltic Business School, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hik:diva-1868.

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<p>In a world that is moving faster and faster, a company’s ability to align to market changes is becoming a major competitive factor. Forecasting enables companies to predict what lies ahead, e.g. trend shifts or market turns, and makes it possible to plan for it. But looking into the future is never an easy task.</p><p>“Prediction is very difficult, especially if it’s about the future.” (Niels Bohr, 1885-1962)</p><p>However, progress in the field of forecasting has shown that it is possible for companies to improve on forecasting practices. This master thesis looks at the sales forecasting p

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Luo, Yi. "DECISION MAKING UNDER UNCERTAINTY IN DYNAMIC MULTI-STAGE ATTACKER-DEFENDER GAMES." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/204331.

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This dissertation presents efficient, on-line, convergent methods to find defense strategies against attacks in dynamic multi-stage attacker-defender games including adaptive learning. This effort culminated in four papers submitted to high quality journals and a book and they are partially published. The first paper presents a novel fictitious play approach to describe the interactions between the attackers and network administrator along a dynamic game. Multi-objective optimization methodology is used to predict the attacker's best actions at each decision node. The administrator also keeps

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Swanepoel, Paul. "A forecasting model for photovoltaic module energy production." Thesis, Nelson Mandela Metropolitan University, 2011. http://hdl.handle.net/10948/1420.

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Energy is of concern for governments and economies all over the world. As conventional methods of energy production are facing the prospect of depleting fossil fuel reserves, economies are facing energy risks. With this tension, various threats arise in terms of energy supply security. A shift from intensive fossil fuel consumption to alternative energy consumption combined with the calculated use of fossil fuels needs to be implemented. Using the energy radiated from the sun and converted to electricity through photovoltaic energy conversion is one of the alternative and renewable sources to

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