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Dissertations / Theses on the topic 'Prediction models'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Haider, Peter. "Prediction with Mixture Models." Phd thesis, Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2014/6961/.

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Learning a model for the relationship between the attributes and the annotated labels of data examples serves two purposes. Firstly, it enables the prediction of the label for examples without annotation. Secondly, the parameters of the model can provide useful insights into the structure of the data. If the data has an inherent partitioned structure, it is natural to mirror this structure in the model. Such mixture models predict by combining the individual predictions generated by the mixture components which correspond to the partitions in the data. Often the partitioned structure is latent

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2

Vaidyanathan, Sivaranjani. "Bayesian Models for Computer Model Calibration and Prediction." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1435527468.

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3

Charraud, Jocelyn, and Saez Adrian Garcia. "Bankruptcy prediction models on Swedish companies." Thesis, Umeå universitet, Företagsekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-185143.

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Bankruptcies have been a sensitive topic all around the world for over 50 years. From their research, the authors have found that only a few bankruptcy studies have been conducted in Sweden and even less on the topic of bankruptcy prediction models. This thesis investigates the performance of the Altman, Ohlson and Zmijewski bankruptcy prediction models. This research investigates all Swedish companies during the years 2017 and 2018. This study has the intention to shed light on some of the most famous bankruptcy prediction models. It is interesting to explore the predictive abilities and usa

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4

Rice, Nigel. "Multivariate prediction models in medicine." Thesis, Keele University, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314647.

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5

Brefeld, Ulf. "Semi-supervised structured prediction models." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2008. http://dx.doi.org/10.18452/15748.

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Das Lernen aus strukturierten Eingabe- und Ausgabebeispielen ist die Grundlage für die automatisierte Verarbeitung natürlich auftretender Problemstellungen und eine Herausforderung für das Maschinelle Lernen. Die Einordnung von Objekten in eine Klassentaxonomie, die Eigennamenerkennung und das Parsen natürlicher Sprache sind mögliche Anwendungen. Klassische Verfahren scheitern an der komplexen Natur der Daten, da sie die multiplen Abhängigkeiten und Strukturen nicht erfassen können. Zudem ist die Erhebung von klassifizierten Beispielen in strukturierten Anwendungsgebieten au

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6

Asterios, Geroukis. "Prediction of Linear Models: Application of Jackknife Model Averaging." Thesis, Uppsala universitet, Statistiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-297671.

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When using linear models, a common practice is to find the single best model fit used in predictions. This on the other hand can cause potential problems such as misspecification and sometimes even wrong models due to spurious regression. Another method of predicting models introduced in this study as Jackknife Model Averaging developed by Hansen & Racine (2012). This assigns weights to all possible models one could use and allows the data to have heteroscedastic errors. This model averaging estimator is compared to the Mallows’s Model Averaging (Hansen, 2007) and model selection by Bayesi

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7

Shrestha, Rakshya. "Deep soil mixing and predictive neural network models for strength prediction." Thesis, University of Cambridge, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.607735.

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8

Grant, Stuart William. "Risk prediction models in cardiovascular surgery." Thesis, University of Manchester, 2014. https://www.research.manchester.ac.uk/portal/en/theses/risk-prediction-models-in-cardiovascular-surgery(1befbc5d-2aa6-4d24-8c32-e635cf55e339).html.

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Objectives: Cardiovascular disease is the leading cause of mortality and morbidity in the developed world. Surgery can improve prognosis and relieve symptoms. Risk prediction models are increasingly being used to inform clinicians and patients about the risks of surgery, to facilitate clinical decision making and for the risk-adjustment of surgical outcome data. The importance of risk prediction models in cardiovascular surgery has been highlighted by the publication of cardiovascular surgery outcome data and the need for risk-adjustment. The overall objective of this thesis is to advance risk

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9

Jones, Margaret. "Point prediction in survival time models." Thesis, University of Newcastle Upon Tyne, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340616.

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10

Monsch, Matthieu (Matthieu Frederic). "Large scale prediction models and algorithms." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/84398.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Operations Research Center, 2013.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 129-132).<br>Over 90% of the data available across the world has been produced over the last two years, and the trend is increasing. It has therefore become paramount to develop algorithms which are able to scale to very high dimensions. In this thesis we are interested in showing how we can use structural properties of a given problem to come up with models applicable in practice, while keeping most of the value of a l

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11

Wanigasekara, Prashan. "Latent state space models for prediction." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/106269.

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Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, System Design and Management Program, Engineering and Management Program, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 95-98).<br>In this thesis, I explore a novel algorithm to model the joint behavior of multiple correlated signals. Our chosen example is the ECG (Electrocardiogram) and ABP (Arterial Blood Pressure) signals from patients in the ICU (Intensive Care Unit). I then use the generated models to predict blood pressure levels of ICU

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12

Smith, Christopher P. "Surrogate models for aerodynamic performance prediction." Thesis, University of Surrey, 2015. http://epubs.surrey.ac.uk/808464/.

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Automatic optimisers can play a vital role in the design and development of engineering systems and processes. However, a lack of available data to guide the search can result in the global optimum solution never being found. Surrogate models can be used to address this lack of data and allow more of the design space to be explored, as well as provide an overall computational saving. In this thesis I have developed two novel long-term prediction methods that investigate the use of ensembles of surrogates to perform predictions of aerodynamic data. The models are built using intermediate comput

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13

Nsolo, Edward. "Prediction models for soccer sports analytics." Thesis, Linköpings universitet, Databas och informationsteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-149033.

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In recent times there has been a substantial increase in research interest of soccer due to an increase of availability of soccer statistics data. With the help of data provider firms, access to historical soccer data becomes more simple and as a result data scientists started researching in the field. In this thesis, we develop prediction models that could be applied by data scientists and other soccer stakeholders. As a case study, we run several machine learning algorithms on historical data from five major European leagues and make a comparison. The study is built upon the idea of investig

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14

Stone, Peter H. "Climate Prediction: The Limits of Ocean Models." MIT Joint Program on the Science and Policy of Global Change, 2004. http://hdl.handle.net/1721.1/4056.

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We identify three major areas of ignorance which limit predictability in current ocean GCMs. One is the very crude representation of subgrid-scale mixing processes. These processes are parameterized with coefficients whose values and variations in space and time are poorly known. A second problem derives from the fact that ocean models generally contain multiple equilibria and bifurcations, but there is no agreement as to where the current ocean sits with respect to the bifurcations. A third problem arises from the fact that ocean circulations are highly nonlinear, but only weakly dissipative,

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15

Faull, Nicholas Eric. "Ensemble climate prediction with coupled climate models." Thesis, University of Oxford, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.442944.

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16

Pasiouras, Fotios. "Development of bank acquisition targets prediction models." Thesis, Coventry University, 2005. http://curve.coventry.ac.uk/open/items/ecf1b00d-da92-9bd2-5b02-fa4fab8afb0c/1.

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This thesis develops a range of prediction models for the purpose of predicting the acquisition of commercial banks in the European Union using publicly available data. Over the last thirty years, there have been approximately 30 studies that have attempted to identify potential acquisition targets, all of them focusing on non-bank sectors. We consider that prediction models developed specifically for the banking industry are essential due to the unusual structure of banks' financial statements, differences in the environment in which banks operate and other specific characteristics of banks t

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17

Gray, Eoin. "Validating and updating lung cancer prediction models." Thesis, University of Sheffield, 2018. http://etheses.whiterose.ac.uk/19206/.

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Lung cancer is a global disease that aﬀect millions of individuals worldwide. Additionally, the disease is beset with a poor 5-year survival rate, a direct consequence of a low early stage diagnosis rate. In an attempt to improve lung cancer prognosis, individuals at high risk of developing lung cancer should be identified for periodic screening. Prediction models are devised to predict an individual’s risk of developing a disease over a specified time period. These can be used to identify high risk individuals and be made publically available to allow individuals’ to be conscience of their ow

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18

Pencina, Karol M. "Quantification of improvement in risk prediction models." Thesis, Boston University, 2012. https://hdl.handle.net/2144/32045.

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Thesis (Ph.D.)--Boston University, 2012.<br>PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you.<br>The identification of new factors in modeling the probability of a binary outcome is the main challenge for statisticians and clinicians who want to improve risk prediction. This motivates researchers

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19

Wang, Yangzhengxuan. "Corporate default prediction : models, drivers and measurements." Thesis, University of Exeter, 2011. http://hdl.handle.net/10036/3457.

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This thesis identifies the optimal set of corporate default drivers and examines the prediction performance of corporate default measurement tools, using a sample of companies in the United States from 1970 to 2009. In the discussion of optimal default drivers, feature selection techniques including the t-test and stepwise methods are used to filter relevant default information collected from previous empirical studies. The optimal default driver information set consists of quantitative parameters from accounting ratios, market indices, macroeconomic indicators, default history, and firm age.

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Mateus, Ana Teresa Moreirinha Vila Fernandes. "Quality management in laboratories- Effciency prediction models." Doctoral thesis, Universidade de Évora, 2021. http://hdl.handle.net/10174/29338.

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In recent years, the choice of quality tools by laboratories has increased significantly. This fact contributed to the growth of competitiveness, requiring a new organizational posture to adapt to the new challenges. In order to obtain competitive advantages in the respective sectors of activity, laboratories have increasingly invested in innovation. In this context, the main objective of this study aims to develop efficiency models for laboratories using tools from the Scientific Area of Artificial Intelligence. Throughout this work, different studies will be presented, carried out in water a

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Cordeiro, Silvio Ricardo. "Distributional models of multiword expression compositionality prediction." Thesis, Aix-Marseille, 2017. http://www.theses.fr/2017AIXM0501/document.

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Les systèmes de traitement automatique des langues reposent souvent sur l'idée que le langage est compositionnel, c'est-à-dire que le sens d'une entité linguistique peut être déduite à partir du sens de ses parties. Cette supposition ne s’avère pas vraie dans le cas des expressions polylexicales (EPLs). Par exemple, une "poule mouillée" n'est ni une poule, ni nécessairement mouillée. Les techniques pour déduire le sens des mots en fonction de leur distribution dans le texte ont obtenu de bons résultats sur plusieurs tâches, en particulier depuis l'apparition des word embeddings. Cependant, la

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22

Cordeiro, Silvio Ricardo. "Distributional models of multiword expression compositionality prediction." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2018. http://hdl.handle.net/10183/174519.

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Sistemas de processamento de linguagem natural baseiam-se com frequência na hipótese de que a linguagem humana é composicional, ou seja, que o significado de uma entidade linguística pode ser inferido a partir do significado de suas partes. Essa expectativa falha no caso de expressões multipalavras (EMPs). Por exemplo, uma pessoa caracterizada como pão-duro não é literalmente um pão, e também não tem uma consistência molecular mais dura que a de outras pessoas. Técnicas computacionais modernas para inferir o significado das palavras com base na sua distribuição no texto vêm obtendo um consider

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23

Zhang, Ruomeng. "Evaluation of Current Concrete Creep Prediction Models." University of Toledo / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1461963600.

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24

Rantalainen, Mattias John. "Multivariate prediction models for bio-analytical data." Thesis, Imperial College London, 2008. http://hdl.handle.net/10044/1/1393.

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Quantitative bio-analytical techniques that enable parallel measurements of large numbers of biomolecules generate vast amounts of information for studying and characterising biological systems. These analytical methods are commonly referred to as omics technologies, and can be applied for measurements of e.g. mRNA transcript, protein or metabolite abundances in a biological sample. The work presented in this thesis focuses on the application of multivariate prediction models for modelling and analysis of biological data generated by omics technologies. Omics data commonly contain up to tens o

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25

Schwiegerling, James Theodore. "Visual performance prediction using schematic eye models." Diss., The University of Arizona, 1995. http://hdl.handle.net/10150/187327.

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The goal of visual modeling is to predict the visual performance or a change in performance of an individual from a model of the human visual system. In designing a model of the human visual system, two distinct functions are considered. The first is the production of an image incident on the retina by the optical system of the eye, and the second is the conversion of this image into a perceived image by the retina and brain. The eye optics are evaluated using raytracing techniques familiar to the optical engineer. The effect of the retinal and brain function are combined with the raytracing r

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26

Gao, Sheng. "Latent factor models for link prediction problems." Paris 6, 2012. http://www.theses.fr/2012PA066056.

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Avec la croissance d'Internet et celle des médias sociaux, les données relationnelles, qui décrivent un ensemble d'objets liés entre eux par différents relations, sont devenues courantes. En conséquence, une grande variété d'applications, telles que les systèmes de recommandation, l'analyse de réseaux sociaux, la fouille de données Web ou la bioinformatique, ont motivé l'étude de techniques d'apprentissage relationnel. Parmi le large éventail de ces techniques, nous traitons dans cette thèse le problème de prédiction de liens. Le problème de la prédiction de liens est une tache fondamentale de

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27

Rossi, A. "PREDICTIVE MODELS IN SPORT SCIENCE: MULTI-DIMENSIONAL ANALYSIS OF FOOTBALL TRAINING AND INJURY PREDICTION." Doctoral thesis, Università degli Studi di Milano, 2017. http://hdl.handle.net/2434/495229.

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Due to the fact that team sports such as football have a complex multidirectional and intermittent nature, an accurate planning of the training workload is needed in order to maximise the athletes’ performance during the matches and reduce their risk of injury. Despite the evaluation of external workloads during trainings and matches has become more and more easier thanks to the advent of the tracking system technologies such as Global Position System (GPS), the planning of the best training workloads aimed to obtain the higher performance during the matches and a lower risk of injury during s

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Eadie, Edward Norman. "Small resource stock share price behaviour and prediction." Title page, contents and abstract only, 2002. http://web4.library.adelaide.edu.au/theses/09CM/09cme11.pdf.

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29

Gamalielsson, Jonas. "Models for Protein Structure Prediction by Evolutionary Algorithms." Thesis, University of Skövde, Department of Computer Science, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-623.

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<p>Evolutionary algorithms (EAs) have been shown to be competent at solving complex, multimodal optimisation problems in applications where the search space is large and badly understood. EAs are therefore among the most promising classes of algorithms for solving the Protein Structure Prediction Problem (PSPP). The PSPP is how to derive the 3D-structure of a protein given only its sequence of amino acids. This dissertation defines, evaluates and shows limitations of simplified models for solving the PSPP. These simplified models are off-lattice extensions to the lattice HP model which has bee

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30

Mousavi, Biouki Seyed Mohammad Mahdi. "Design and performance evaluation of failure prediction models." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/25925.

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Prediction of corporate bankruptcy (or distress) is one of the major activities in auditing firms’ risks and uncertainties. The design of reliable models to predict distress is crucial for many decision-making processes. Although a variety of models have been designed to predict distress, the relative performance evaluation of competing prediction models remains an exercise that is unidimensional in nature. To be more specific, although some studies use several performance criteria and their measures to assess the relative performance of distress prediction models, the assessment exercise of c

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Gendron-Bellemare, Marc. "Learning prediction and abstraction in partially observable models." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=18471.

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Markov models have been a keystone in Artificial Intelligence for many decades. However, they remain unsatisfactory when the environment modeled is partially observable. There are pathological examples where no history of fixed length is sufficient for accurate deci- sion making. On the other hand, working with a hidden state (such as in POMDPs) has a high computational cost. In order to circumvent this problem, I suggest the use of a context- based model. My approach replaces strict transition probabilities by a linear approximation of probability distributions. The method proposed prov

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Svensson, Jacob. "Boundary Layer Parametrization in Numerical Weather Prediction Models." Licentiate thesis, Stockholms universitet, Meteorologiska institutionen (MISU), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-117134.

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Numerical weather prediction (NWP) and climate models have shown to have a challenge to correctly simulate stable boundary layers and diurnal cycles. This aim of this study is to evaluate, describe and give suggestions for improvements of the descriptions of stable boundary layers in operational NWP models. Two papers are included. Paper I focuses on the description of the surface and the interactions between the surface and the boundary layer in COAMPSR, a regional NWP model. The soil parametrization showed to be of great importance to the structure of the boundary layer. Moreover, it showed

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33

Voigt, Alexander. "Mass spectrum prediction in non-minimal supersymmetric models." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-152797.

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Supersymmetry is an attractive extension of the Standard Model (SM) of particle physics. The minimal supersymmetric extension (MSSM) provides gauge coupling unification, a dark matter candidate particle and can explain the breaking of the electroweak symmetry dynamically. However, it suffers from the little hierarchy and the mu-problem. Non-minimal supersymmetric extensions of the SM with a larger particle content or a higher symmetry can evade the problems of the MSSM. Such models may be well-motivated by Grand Unified Theories (GUTs) and can provide a rich new phenomenology with an extended

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Hawkes, Richard Nathanael. "Linear state models for volatility estimation and prediction." Thesis, Brunel University, 2007. http://bura.brunel.ac.uk/handle/2438/7138.

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This thesis concerns the calibration and estimation of linear state models for forecasting stock return volatility. In the first two chapters I present aspects of financial modelling theory and practice that are of particular relevance to the theme of this present work. In addition to this I review the literature concerning these aspects with a particular emphasis on the area of dynamic volatility models. These chapters set the scene and lay the foundations for subsequent empirical work and are a contribution in themselves. The structure of the models employed in the application chapters 4,5 a

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AMARAL, BERNARDO HALLAK. "PREDICTION OF FUTURE VOLATILITY MODELS: BRAZILIAN MARKET ANALYSIS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2012. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=20458@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>Realizar a previsão de volatilidade futura é algo que intriga muitos estudiosos, pesquisadores e pessoas do mercado financeiro. O modelo e a metodologia utilizados no cálculo são fundamentais para o apreçamento de opções e dependendo das variáveis utilizadas, o resultado se torna muito sensível, propiciando resultados diferentes. Tudo isso pode causar cálculos imprecisos e estruturação de estratégias erradas de compra e venda de ações e opções por empresas e investidores. Por isso, o objetivo deste trabalho é utilizar alguns modelos para o

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Qarmalah, Najla Mohammed A. "Finite mixture models : visualisation, localised regression, and prediction." Thesis, Durham University, 2018. http://etheses.dur.ac.uk/12486/.

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Initially, this thesis introduces a new graphical tool, that can be used to summarise data possessing a mixture structure. Computation of the required summary statistics makes use of posterior probabilities of class membership obtained from a fitted mixture model. In this context, both real and simulated data are used to highlight the usefulness of the tool for the visualisation of mixture data in comparison to the use of a traditional boxplot. This thesis uses localised mixture models to produce predictions from time series data. Estimation method used in these models is achieved using a kern

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Li, Edwin. "LSTM Neural Network Models for Market Movement Prediction." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231627.

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Interpreting time varying phenomena is a key challenge in the capital markets. Time series analysis using autoregressive methods has been carried out over the last couple of decades, often with reassuring results. However, such methods sometimes fail to explain trends and cyclical fluctuations, which may be characterized by long-range dependencies or even dependencies between the input features. The purpose of this thesis is to investigate whether recurrent neural networks with LSTM-cells can be used to capture these dependencies, and ultimately be used as a complement for index trading decisi

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Rogge-Solti, Andreas, Laura Vana, and Jan Mendling. "Time Series Petri Net Models - Enrichment and Prediction." CEUR Workshop Proceedings, 2015. http://epub.wu.ac.at/5394/1/paper8.pdf.

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Operational support as an area of process mining aims to predict the temporal performance of individual cases and the overall business process. Although seasonal effects, delays and performance trends are well-known to exist for business processes, there is up until now no prediction model available that explicitly captures this. In this paper, we introduce time series Petri net models. These models integrate the control flow perspective of Petri nets with time series prediction. Our evaluation on the basis of our prototypical implementation demonstrates the merits of this model in term

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Fernando, Warnakulasuriya Chandima. "Blood Glucose Prediction Models for Personalized Diabetes Management." Thesis, North Dakota State University, 2018. https://hdl.handle.net/10365/28179.

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Effective blood glucose (BG) control is essential for patients with diabetes. This calls for an immediate need to closely keep track of patients' BG level all the time. However, sometimes individual patients may not be able to monitor their BG level regularly due to all kinds of real-life interference. To address this issue, in this paper we propose machine-learning based prediction models that can automatically predict patients BG level based on their historical data and known current status. We take two approaches, one for predicting BG level only using individual's data and second is to use

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Bratières, Sébastien. "Non-parametric Bayesian models for structured output prediction." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/274973.

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Structured output prediction is a machine learning tasks in which an input object is not just assigned a single class, as in classification, but multiple, interdependent labels. This means that the presence or value of a given label affects the other labels, for instance in text labelling problems, where output labels are applied to each word, and their interdependencies must be modelled. Non-parametric Bayesian (NPB) techniques are probabilistic modelling techniques which have the interesting property of allowing model capacity to grow, in a controllable way, with data complexity, while maint

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Gorthi, Swathi. "Prediction Models for Estimation of Soil Moisture Content." DigitalCommons@USU, 2011. https://digitalcommons.usu.edu/etd/1090.

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This thesis introduces the implementation of different supervised learning techniques for producing accurate estimates of soil moisture content using empirical information, including meteorological and remotely sensed data. The models thus developed can be extended to be used by the personal remote sensing systems developed in the Center for Self-Organizing Intelligent Systems (CSOIS). The dfferent models employed extend over a wide range of machine-learning techniques starting from basic linear regression models through models based on Bayesian framework. Also, ensembling methods such as bagg

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Cutugno, Carmen. "Statistical models for the corporate financial distress prediction." Thesis, Università degli Studi di Catania, 2011. http://hdl.handle.net/10761/283.

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Kumar, Akhil. "Budget-Related Prediction Models in the Business Environment with Special Reference to Spot Price Predictions." Thesis, North Texas State University, 1986. https://digital.library.unt.edu/ark:/67531/metadc331533/.

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The purpose of this research is to study and improve decision accuracy in the real world. Spot price prediction of petroleum products, in a budgeting context, is the task chosen to study prediction accuracy. Prediction accuracy of executives in a multinational oil company is examined. The Brunswik Lens Model framework is used to evaluate prediction accuracy. Predictions of the individuals, the composite group (mathematical average of the individuals), the interacting group, and the environmental model were compared. Predictions of the individuals were obtained through a laboratory experiment i

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Sawert, Marcus. "Predicting deliveries from suppliers : A comparison of predictive models." Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-39314.

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In the highly competitive environment that companies find themselves in today, it is key to have a well-functioning supply chain. For manufacturing companies, having a good supply chain is dependent on having a functioning production planning. The production planning tries to fulfill the demand while considering the resources available. This is complicated by the uncertainties that exist, such as the uncertainty in demand, in manufacturing and in supply. Several methods and models have been created to deal with production planning under uncertainty, but they often overlook the complexity in th

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Wiseman, Scott. "Bayesian learning in graphical models." Thesis, University of Kent, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.311261.

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Almeida, Mara Elisabeth Monteiro. "Bankruptcy prediction models: an analysis for Portuguese SMEs." Master's thesis, 2020. http://hdl.handle.net/1822/67108.

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Projeto de mestrado em Finanças<br>This project intends to test the models developed by Altman (1983) and Ohlson (1980) and assess the predictive capacity of these models when applied to a dataset of Portuguese SMEs. This work is the result of a partnership with a Portuguese startup called nBanks, which dedicates its activity to providing financial services to its customers. In this sense, this project will allow nBanks to develop a new and innovative instrument that will allow its customers to access their probability or risk of default. The data were collected from the Amadeus database,

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Yuan, Yan. "Prediction Performance of Survival Models." Thesis, 2008. http://hdl.handle.net/10012/3974.

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Statistical models are often used for the prediction of future random variables. There are two types of prediction, point prediction and probabilistic prediction. The prediction accuracy is quantified by performance measures, which are typically based on loss functions. We study the estimators of these performance measures, the prediction error and performance scores, for point and probabilistic predictors, respectively. The focus of this thesis is to assess the prediction performance of survival models that analyze censored survival times. To accommodate censoring, we extend the inverse proba

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Auerbach, Jonathan Lyle. "Some Statistical Models for Prediction." Thesis, 2020. https://doi.org/10.7916/d8-gcvm-jj03.

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This dissertation examines the use of statistical models for prediction. Examples are drawn from public policy and chosen because they represent pressing problems facing U.S. governments at the local, state, and federal level. The first five chapters provide examples where the perfunctory use of linear models, the prediction tool of choice in government, failed to produce reasonable predictions. Methodological flaws are identified, and more accurate models are proposed that draw on advances in statistics, data science, and machine learning. Chapter 1 examines skyscraper construction, where the

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Lin, Hsin-Yin, and 林欣穎. "The Application of Grey Prediction Models to Depreciation Expense Prediction." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/d6u94c.

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碩士<br>國立臺北科技大學<br>自動化科技研究所<br>103<br>Earnings per share (EPS) serves an important indicator for investors to analyze listed companies. Business owners with good reputation and accountability also consider it is important to achieve their annual EPS growth rate. Higher EPS means the company is high profitability per of unit capital, the company has better ability than the other competitors. That means it can use fewer resources to create higher profit. Among the factors affecting a listed company&;#39;s earnings per share, where the cost of the item is depreciation. Depreciation is the cost tha

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Dendamrongvit, Thidarat. "Development of a posture prediction model." Thesis, 2002. http://hdl.handle.net/1957/30990.

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Biomechanical models have been used in designing human work environments to evaluate potential risks to workers before a work environment is constructed. In order for work environments to be modeled correctly, most biomechanical models require as input, an accurate body posture of the worker. This information can be obtained by, either measuring the posture of workers for the task of interest, or estimating the posture. This research explores methods to estimate working postures by developing a model that can predict a worker's posture. The model in this thesis represents the body of the worke

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