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Dissertations / Theses on the topic 'Machined Rules'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Wang, Olivier. "Adaptive Rules Model : Statistical Learning for Rule-Based Systems." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLX037/document.

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Les Règles Métiers (Business Rules en anglais, ou BRs) sont un outil communément utilisé dans l’industrie pour automatiser des prises de décisions répétitives. Le problème de l’adaptation de bases de règles existantes à un environnement en constante évolution est celui qui motive cette thèse. Des techniques existantes d’Apprentissage Automatique Supervisé peuvent être utilisées lorsque cette adaptation se fait en toute connaissance de la décision correcte à prendre en toute circonstance. En revanche, il n’existe actuellement aucun algorithme, qu’il soit théorique ou pratique, qui puisse résoud

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Dugast, Loic. "Introducing corpus-based rules and algorithms in a rule-based machine translation system." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/8249.

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Machine translation offers the challenge of automatically translating a text from one natural language into another. Statistical methods - originating from the field of information theory - have shown to be a major breakthrough in the field of machine translation. Prior to this paradigm, many systems had been developed following a rule-based approach. This denotes a system based on a linguistic description of the languages involved and of how translation occurs in the mind of the (human) translator. Statistical models on the contrary use empirical means and may work with very little linguistic

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3

Berry, Eric Dean. "Randomization testing of machine induced rules." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1995. http://handle.dtic.mil/100.2/ADA304271.

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Thesis (M.S. in Information Technology Management) Naval Postgraduate School, September 1995.<br>"September 1995." Thesis advisor(s): B. Ramesh, William J. Haga. Includes bibliographical references. Also available online.

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4

Whelan, Kenneth Edward. "Inducing succinct rules in machine learning problems." Thesis, Abertay University, 1998. https://rke.abertay.ac.uk/en/studentTheses/9d19485d-2002-40b9-a1c4-9ab219105784.

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Machine Learning techniques, in particular induction algorithms, have been applied to the field of expert systems development in an effort to overcome the knowledge acquisition bottleneck. Many different induction algorithms have been developed. These utilise a number of different knowledge representations: e.g decision trees and rules. The rule based representation includes systems which utilise both propositional and predicate logic languages. Decision tree and rule based induction employ different knowledge acquisition mechanisms, however both strategies tend to induce complex and inaccurat

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Mac, Kinney Romero Rene. "Inducing rules in a higher-order framework." Thesis, University of Bristol, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.247199.

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6

Huszár, Ferenc. "Scoring rules, divergences and information in Bayesian machine learning." Thesis, University of Cambridge, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.648333.

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Trujillo, Indalecio Arturo. "Lexicalist machine translation of spatial prepositions." Thesis, University of Cambridge, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388507.

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8

Garg, Aditie. "Designing Reactive Power Control Rules for Smart Inverters using Machine Learning." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/83558.

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Due to increasing penetration of solar power generation, distribution grids are facing a number of challenges. Frequent reverse active power flows can result in rapid fluctuations in voltage magnitudes. However, with the revised IEEE 1547 standard, smart inverters can actively control their reactive power injection to minimize voltage deviations and power losses in the grid. Reactive power control and globally optimal inverter coordination in real-time is computationally and communication-wise demanding, whereas the local Volt-VAR or Watt-VAR control rules are subpar for enhanced grid service

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9

Liu, Pengyu. "Extracting Rules from Trained Machine Learning Models with Applications in Bioinformatics." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/264678.

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京都大学<br>新制・課程博士<br>博士(情報学)<br>甲第23397号<br>情博第766号<br>新制||情||131(附属図書館)<br>京都大学大学院情報学研究科知能情報学専攻<br>(主査)教授阿久津達也, 教授山本章博, 教授鹿島久嗣<br>学位規則第4条第1項該当<br>Doctor of Informatics<br>Kyoto University<br>DFAM

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10

Wainwright, Elizabeth Lorraine, and Elizabeth Lorraine Wainwright. "Machine Recognition of Rule-Based Phonological Patterns." Thesis, The University of Arizona, 2017. http://hdl.handle.net/10150/625234.

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This thesis is project-oriented, with the goal of the research being to create a computer program that will take a set of words in a language written in the International Phonetic Alphabet (IPA) and two sets of phonemes where one undergoes a phonological change to the other and return a phonological rule describing this data. The program was written in Python. It included several functions as well as a new class termed "Phoneme" to facilitate the storage of phonemic features. A reference was made of Phoneme objects for the program to refer to for feature information while analyzing a data set.

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CHAVES, ADRIANA DA COSTA FERREIRA. "FUZZY RULES EXTRACTION FROM SUPPORT VECTOR MACHINES (SVM) FOR MULTI-CLASS CLASSIFICATION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2006. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=9191@1.

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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>Este trabalho apresenta a proposta de um novo método para a extração de regras fuzzy de máquinas de vetor suporte (SVMs) treinadas para problemas de classificação. SVMs são sistemas de aprendizado baseados na teoria estatística do aprendizado e apresentam boa habilidade de generalização em conjuntos de dados reais. Estes sistemas obtiveram sucesso em vários tipos de problemas. Entretanto, as SVMs, da mesma forma que redes neurais (RN), geram um modelo caixa preta, isto é, um modelo que não explica o processo pelo qual sua

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Kopru, Selcuk. "Coupling Speech Recognition And Rule-based Machine Translation." Phd thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12610001/index.pdf.

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The objective of this thesis was to study the coupling of automatic speech recognition (ASR) systems with rule-based machine translation (MT) systems. In this thesis, a unique approach to integrating ASR with MT for speech translation (ST) tasks was proposed. The proposed approach is unique, essentially because it includes the rst rule-based MT system that can process speech data in a word graph format. Compared to other rule-based MT systems, our system processes both a word graph and a stream of words. Thus, the suggested integration method of the ASR and the rule-based MT system is more det

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13

Tyers, Francis M. "Feasible lexical selection for rule-based machine translation." Doctoral thesis, Universidad de Alicante, 2013. http://hdl.handle.net/10045/35848.

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Lindeberg, James. "Simplification of Swedish Text by Monolingual Machine Translation Transformation Rules for Simplified Swedish." Thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-352897.

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Discussions on the concept of ”Klarspråk” and ”Lättläst” are major topics in Sweden at the moment with efforts towards increasing readability of government organization information in the project ”Begriplig Text”. In the field of natural language processing, a lot of efforts have gone into text simplification. This thesis examines the possibility of using hand crafted transfer and generation rules to increase the readability of text through monolingual machine translation. Transfer and generation rules were developed that handle Swedish grammatical structures including explicitivity and word o

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Ren, Lu. "Rule extraction from Support Vector Machines : a geometric approach." Thesis, City University London, 2008. http://openaccess.city.ac.uk/11917/.

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Despite the success of connectionist systems in prediction and classification problems, critics argue that the lack of symbol processing and explanation capability makes them less competitive than symbolic systems. Rule extraction from neural networks makes the interpretation of the behaviour of connectionist networks possible by relating sub-symbolic and symbolic processing. However, most rule extraction methods focus only on specific neural network architectures and present limited generalization performance. Support Vector Machine is an unsupervised learning method that has been recently ap

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Liu, Han. "Rule based systems for classification in machine learning context." Thesis, University of Portsmouth, 2015. https://researchportal.port.ac.uk/portal/en/theses/rule-based-systems-for-classification-in-machine-learning-context(1790225c-ceb1-48d3-9e05-689edbfa3ef1).html.

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This thesis introduces a unified framework for design of rule based systems for classification tasks, which consists of the operations of rule generation, rule simplification and rule representation. This thesis also stresses the importance of combination of different rule learning algorithms through ensemble learning approaches. For the three operations mentioned above, novel approaches are developed and validated by comparing with existing ones for advancing the performance of using this framework. In particular, for rule generation, Information Entropy Based Rule Generation is developed and

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Owens, Kelti. "The Evaluation of The Role of Self-Rules on Gambling Behaviors Using a Slot Machine." OpenSIUC, 2015. https://opensiuc.lib.siu.edu/theses/1617.

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Current research on problem gambling has focused primarily on how the gambling mechanism effects a person's problem gambling. The purpose of the current study was to investigate the effects of a second slot machine on gambling behavior. This would show that other contingencies in the environment affect a gambler's behavior. A within and between-subjects group design was used with 26 participants. Experimental group participants experienced a baseline condition, a winning condition and a losing condition. Control group participants experienced three sessions of baseline condition. During the wi

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18

Stackhouse, Christian Paul 1960. "AN ADAPTIVE RULE-BASED SYSTEM." Thesis, The University of Arizona, 1987. http://hdl.handle.net/10150/276534.

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Adaptive systems are systems whose characteristics evolve over time to improve their performance at a task. A fairly new area of study is that of adaptive rule-based systems. The system studied for this thesis uses meta-knowledge about rules, rulesets, rule performance, and system performance in order to improve its overall performance in a problem domain. An interesting and potentially important phenomenon which emerged is that the performance the system learns while solving a problem appears to be limited by an inherent break-even level of complexity. That is, the cost to the system of acqui

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Firebanks-Quevedo, Daniel. "Machine Learning? In MY Election? It's More Likely Than You Think: Voting Rules via Neural Networks." Oberlin College Honors Theses / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1589820416539647.

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Melero, Nogués Maria Teresa. "Combining machine learning and rule-based approaches in Spanish syntactic generation." Doctoral thesis, Universitat Pompeu Fabra, 2006. http://hdl.handle.net/10803/7501.

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Aquesta tesi descriu una gramàtica de Generació que combina regles escrites a mà i tècniques d'aprenentatge automàtic. Aquesta gramàtica pertany a un sistema de Traducció Automàtica de qualitat comercial desenvolupat a Microsoft Research. La primera part presenta la gramàtica i les principals estratègies lingüístiques que aquesta gramàtica implementa. Els requeriments de robustesa que reclama l'ús real del sistema de TA, exigeix del Generador un esforç suplementari que es resol afegint un nivell de pre-generació, capaç de garantir la integritat de l'entrada, sense incorporar elements ad-hoc en

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21

Pihlqvist, Fredrik, and Benedith Mulongo. "USING RULE-BASED METHODS AND MACHINE LEARNING FOR SHORT ANSWER SCORING." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-232070.

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Automatiskt rättning av korta texter är ett område som spänner allt från naturlig språkbehandling till maskininlärning. Projektet behandlar maskininlärning för att förutsäga korrektheten av svar i fritext. Naturlig språkbehandling används för att analysera text och utvinna viktiga underliggande relationer i texten. Det finns idag flera approximativa lösningar för automatiskt rättning av korta svar i fritext. Två framstående metoder är maskininlärning och regelbaserad metod. Vi kommer att framföra en alternativ metod som kombinerar maskininlärning med en regelbaserad metod för att approximativt

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22

Jarvis, Matthew P. "Applying machine learning techniques to rule generation in intelligent tutoring systems." Link to electronic thesis, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0429104-112724.

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Thesis (M.S.)--Worcester Polytechnic Institute.<br>Keywords: Intelligent Tutoring Systems; Model Tracing; Machine Learning; Artificial Intelligence; Programming by Demonstration. Includes bibliographical references.

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23

Carse, Brian. "Artificial evolution of fuzzy and temporal rule based systems." Thesis, University of the West of England, Bristol, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267551.

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24

Le, Besnerais Jean. "Reduction of magnetic noise in PWM-supplied induction machines : low-noise design rules and multi-objective optimisation." Ecole Centrale de Lille, 2008. http://tel.archives-ouvertes.fr/docs/00/34/87/30/PDF/Reduction_of_magnetic_noise_emitted_by_PWM-fed_induction_machines.pdf.

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Cette thèse porte sur la réduction du bruit audible d’origine magnétique émis par les machines asynchrones alimentées par modulation de largeur d’impulsion (MLI), et plus particulièrement par les moteurs de traction ferroviaire. Dans une première partie, une vue générale des travaux de modélisation vibro-acoustique des machines asynchrones et de leurs hypothèses est donnée. L’ensemble des règles de conception silencieuse existantes est présenté, et les effets des variables de conception du moteur et de l’onduleur sur le bruit sont rapportés, ainsi que les travaux portant sur la conception opti

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Cavina, Eugenio. "GEAR: una piattaforma Big Data per l'elaborazione di stream di dati attraverso Machine Learning e Business Rules." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20416/.

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Nel panorama digitale degli ultimi anni, l’utilizzo dei pagamenti elettronici è in continua crescita. La conseguente delibera di regolamentazioni per la tutela dei consumatori implica anche l’utilizzo di sistemi di Online Fraud Detection (OFD) in grado di gestire grandi quantità di dati. La tesi parte dai sistemi OFD (tipicamente proprietari) per creare una soluzione più generale rispetto al dominio specifico e con tecnologie open source. I sistemi di OFD presentano infatti caratteristiche generalizzabili e riutilizzabili in domini applicativi diversi dai pagamenti elettronici e queste sono st

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Wicker, Jerome. "Crystallization properties of molecular materials : prediction and rule extraction by machine learning." Thesis, University of Oxford, 2017. https://ora.ox.ac.uk/objects/uuid:34beef4e-e499-4248-8fa6-7e8d8344f02c.

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Crystallization is an increasingly important process in a variety of applications from drug development to single crystal X-ray diffraction structure determination. However, while there is a good deal of research into prediction of molecular crystal structure, the factors that cause a molecule to be crystallizable have so far remained poorly understood. The aim of this project was to answer the seemingly straightforward question: can we predict how easily a molecule will crystallize? The Cambridge Structural Database contains almost a million examples of materials from the scientific literatur

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Sánchez-Martínez, Felipe. "Using unsupervised corpus-based methods to build rule-based machine translation systems." Doctoral thesis, Universidad de Alicante, 2008. http://hdl.handle.net/10045/13879.

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Catrone, Rocco Giovanni. "Relational training of contextual cues and self-rule formation in simulated slot machines." OpenSIUC, 2015. https://opensiuc.lib.siu.edu/theses/1795.

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Between 1% and 1.4% of people who engage in gambling behaviors lead to disordered or pathological gambling (Whiting & Dixon, 2015), while 44% of all money spent on legal gambling is done so with slot machines (Choliz, 2010). Various behavioral concepts have been theorized as a possible source of gambling addition; losses disguised as wins (LDWs), near-miss, gamblers’ fallacy, illusions of control, and verbally constructed self-rules related to these topics. The current study sought to extend the previous research on condition discrimination in altering slot machine preference while also analyz

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Soltan-Zadeh, Yasaman. "Improved rule-based document representation and classification using genetic programming." Thesis, Royal Holloway, University of London, 2011. http://repository.royalholloway.ac.uk/items/479a1773-779b-8b24-b334-7ed485311abe/8/.

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Anyango, Stephen Omondi Otieno. "VisuNet: Visualizing Networks of feature interactions in rule-based classifiers." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-296336.

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Eldbib, Khaled. "Design and analysis of rule induction systems." Thesis, University of Birmingham, 2016. http://etheses.bham.ac.uk//id/eprint/6841/.

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The RULES family of algorithms is reviewed in this work and the drawback of the variation in their generalisation performance is investigated. This results in a new data ordering method (DOM) for the RULES family of inductive learning algorithms. DOM is based on the selection of the most representative example; the method has been tested as a pre-processing stage for many data sets and has shown promising results. Another difficulty faced is the growing size of training data sets, which results in long algorithm execution times and less compact generated rules. In this study a new data sorting

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Kliegr, Tomas. "Effect of cognitive biases on human understanding of rule-based machine learning models." Thesis, Queen Mary, University of London, 2017. http://qmro.qmul.ac.uk/xmlui/handle/123456789/31851.

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This thesis investigates to what extent do cognitive biases a ect human understanding of interpretable machine learning models, in particular of rules discovered from data. Twenty cognitive biases (illusions, e ects) are analysed in detail, including identi cation of possibly e ective debiasing techniques that can be adopted by designers of machine learning algorithms and software. This qualitative research is complemented by multiple experiments aimed to verify, whether, and to what extent, do selected cognitive biases in uence human understanding of actual rule learning results. Two experime

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Mostofian, Nasrin. "A Study on Manual and Automatic Evaluation Procedures and Production of Automatic Post-editing Rules for Persian Machine Translation." Thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-325818.

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Evaluation of machine translation is an important step towards improving MT. One way to evaluate the output of MT is to focus on different types of errors occurring in the translation hypotheses, and to think of possible solutions to fix those errors. An error categorization is a rather beneficent tool that makes it easy to analyze the translation errors and can also be utilized to manually generate post-editing rules to be applied automatically to the product of machine translation. In this work, we define a categorization for the errors occurring in Swedish--Persian machine translation by an

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Ben, Yahia Wided. "Contribution à la sécurité d'un système Homme-Agroéquipement : spécification d'un générateur de plans d'actions alternatifs pour l'analyse d'erreurs humaines." Thesis, Valenciennes, 2012. http://www.theses.fr/2012VALE0009/document.

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Les travaux de cette thèse portent sur l’élaboration d’une approche d’anticipation des comportements possibles de l’opérateur humain lorsqu’il ne respecte pas certaines règles de sécurité. Le non-respect des règles de sécurité, considéré comme une erreur humaine, constitue la source majeure d’incidents/accidents dans le domaine des agroéquipements. Ce domaine caractérisé par un manque de formalisation de son REX. L’approche proposée consiste à définir une méthodologie permettant de proposer des plans d’actions humaines possibles résultant d’un non-respect des règles de sécurité et de les évalu

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Haghighi, Mona. "Rule-based Risk Monitoring Systems for Complex Datasets." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6248.

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In this dissertation we present rule-based machine learning methods for solving problems with high-dimensional or complex datasets. We are applying decision tree methods on blood-based biomarkers and neuropsychological tests to predict Alzheimer’s disease in its early stages. We are also using tree-based methods to identify disparity in dementia related biomarkers among three female ethnic groups. In another part of this research, we tried to use rule-based methods to identify homogeneous subgroups of subjects who share the same risk patterns out of a heterogeneous population. Finally, we appl

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Weitnauer, Erik [Verfasser]. "Interactions between perception and rule-construction in human and machine concept learning / Erik Weitnauer." Bielefeld : Universitätsbibliothek Bielefeld, 2016. http://d-nb.info/1084884720/34.

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Pic, Romain. "Statistical postprocessing of ensemble forecasts : theory, application in weather forecasting and verification." Electronic Thesis or Diss., Bourgogne Franche-Comté, 2024. http://www.theses.fr/2024UBFCD018.

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Cette thèse porte sur l'utilisation de méthodes de post-traitement statistiques dans le but d'améliorer les prévisions d'ensemble. Les prévisions d'ensemble sont des prévisions composées de différents membres dont la diversité tente de capturer l'incertitude liée à la prédiction. Les prévisions d'ensemble souffrent de biais et de sous-dispersion et un post-traitement est donc nécessaire afin d'améliorer leur performance. D'un point de vue théorique, cette thèse apporte des résultats sur le taux de convergence en régression distributionnelle en termes de continuous ranked probability score. De

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Postovskaya, Anna. "Rule-based machine learning for prediction of Macaca mulatta SIV-vaccination outcome using transcriptome profiles." Thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-440182.

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One of the reasons, why the development of an effective HIV vaccine remains challenging, is the lack of understanding of potential vaccination-induced protection mechanisms. In the present study, Rhesus Macaques (Macaca mulatta) gene expression profiles obtained during vaccination with promising candidate vaccines against Simian Immunodeficiency Virus (SIV) were processed with a rule-based supervised machine learning approach to analyze the effects of vaccine combination treatment. The findings from constructed rule-based classifiers suggest that the immune response against SIV builds up throu

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Henley, Maia S. "The use of context-free grammar in support of Slovak-English rule-based machine translation." Connect to Electronic Thesis (CONTENTdm), 2008. http://worldcat.org/oclc/441973910/viewonline.

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NEMBRINI, STEFANO. "Machine Learning Methods for Feature Selection and Rule Extraction in Genome-wide Association Studies (GWASs)." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/43581.

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Tree-based ensembles have recently gained popularity in genome-wide association studies (GWASs) because particularly suited to discover interactions and non-linear effects. In this context, it is particularly important to discover a small subset of single-nucleotide polymorphisms (SNPs) associated to the outcome of interest (feature selection phase), as well as to provide results that are interpretable (rule extraction phase). Using a dataset of 300K SNPs from a previous study, we propose a method for feature selction based on the use of Random Forests in a two-stage approach in order to se

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Bergdorf, Johan. "Machine learning and rule induction in invoice processing : Comparing machine learning methods in their ability to assign account codes in the bookkeeping process." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-235931.

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Companies with more than 3 million SEK in revenue per year are by law in Sweden required to bookkeep invoices as soon as the invoice arrives after a purchase. One part in this bookkeeping process is to choose which accounts to be credited for every received invoice. This is a time-consuming process which demands to find the right account codes for every invoice depending on a number of factors. This thesis investigates how well machine learning can manage this process. Specifically, it is investigated how well machine learning methods that produce unordered rule sets can classify invoice data

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Pham, Dinh. "A novel rule induction algorithm with improved handling of continuous valued attributes." Thesis, Cardiff University, 2012. http://orca.cf.ac.uk/34591/.

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Machine learning programs can automatically learn to recognise complex patterns and make intelligent decisions based on data. Machine learning has become a powerful tool for data mining. A great deal of research in machine learning has focused on concept learning or classification learning. Among the various machine learning approaches that have been developed for classification, inductive learning from examples is the most commonly adopted in real-life applications. Due to non-uniform data formats and huge volume of data, it is a challenge for scientists across different disciplines to optimi

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Hasan, S. M. Kamrul Engineering &amp Information Technology Australian Defence Force Academy UNSW. "Evolutionary algorithms for solving job-shop scheduling problems in the presence of process interruptions." Awarded by:University of New South Wales - Australian Defence Force Academy. Engineering & Information Technology, 2009. http://handle.unsw.edu.au/1959.4/43768.

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In this thesis, the Job Shop Scheduling Problem (JSSP) is the problem of interest. The classical JSSP is well-known as an NP-hard problem. Although with current computational capabilities, the small problems are solvable using deterministic methods, it is out of reach when they are larger in size. The complexity of JSSP is further increased when process interruptions, such as machine breakdown and/or machine unavailability, are introduced. Over the last few decades, several stochastic algorithms have been proposed to solve JSSPs. However, none of them are suitable for all kinds of probl

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Ganduri, Chandrasekhar. "Rule Driven Job-Shop Scheduling Derived from Neural Networks through Extraction." Ohio University / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1102537257.

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Persaud, Felicia Nafeeza. "In Search of Computer Music Analysis: Music Information Retrieval, Optimization, and Machine Learning from 2000-2016." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/38007.

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My thesis aims to critically examine three methods in the current state of Computer Music Analysis. I will concentrate on Music Information Retrieval, Optimization, and Machine Learning. My goal is to describe and critically analyze each method, then examine the intersection of all three. I will start by looking at David Temperley’s The Cognition of Basic Musical Structures (2001) which offers an outline of major accomplishments before the turn of the 21st century. This outline will provide a method of organization for a large portion of the thesis. I will conclude by explaining the most rece

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Wakhare, Mayur M. "Rule Based Setup and Fixture Planning for Prismatic Parts on 3-Axis and 4-Axis Milling Machines." Ohio University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1470758431.

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Caseli, Helena de Medeiros. "Indução de léxicos bilíngües e regras para a tradução automática." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-29082007-090905/.

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A Tradução Automática (TA) -- tradução de uma língua natural (fonte) para outra (alvo) por meio de programas de computador -- é uma tarefa árdua devido, principalmente, à necessidade de um conhecimento lingüístico aprofundado das duas (ou mais) línguas envolvidas para a construção de recursos, como gramáticas de tradução, dicionários bilíngües etc. A escassez de recursos lingüísticos, e mesmo a dificuldade em produzi-los, geralmente são fatores limitantes na atuação dos sistemas de TA, restringindo-os, por exemplo, quanto ao domínio de aplicação. Neste contexto, diversos métodos vêm sendo prop

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Zhang, Zhan. "Developing a Unified Perspective on the Role of Multiresolution in Machine Intelligence Tasks." Case Western Reserve University School of Graduate Studies / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=case1102085255.

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Hu, Hae-Jin. "Design of Comprehensible Learning Machine Systems for Protein Structure Prediction." Digital Archive @ GSU, 2007. http://digitalarchive.gsu.edu/cs_diss/22.

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With the efforts to understand the protein structure, many computational approaches have been made recently. Among them, the Support Vector Machine (SVM) methods have been recently applied and showed successful performance compared with other machine learning schemes. However, despite the high performance, the SVM approaches suffer from the problem of understandability since it is a black-box model; the predictions made by SVM cannot be interpreted as biologically meaningful way. To overcome this limitation, a new association rule based classifier PCPAR was devised based on the existing cla

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Abar, Orhan. "Rule Mining and Sequential Pattern Based Predictive Modeling with EMR Data." UKnowledge, 2019. https://uknowledge.uky.edu/cs_etds/85.

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Electronic medical record (EMR) data is collected on a daily basis at hospitals and other healthcare facilities to track patients’ health situations including conditions, treatments (medications, procedures), diagnostics (labs) and associated healthcare operations. Besides being useful for individual patient care and hospital operations (e.g., billing, triaging), EMRs can also be exploited for secondary data analyses to glean discriminative patterns that hold across patient cohorts for different phenotypes. These patterns in turn can yield high level insights into disease progression with inte

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