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Thèses sur le sujet « Predictive Intelligence »

Auteur : Grafiati

Publié le 2 juin 2025

Mis à jour le 31 juillet 2025

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1

St, Clair Ronald Benjamin. "Predictive failure? Intelligence-gathering and the FLQ." Thesis, University of Ottawa (Canada), 2005. http://hdl.handle.net/10393/27045.

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It has been the Canadian federal government's consistent position that the decision to invoke the War Measures Act had been arrived at due to a lack of available intelligence on the FLQ. They contend that sufficient advance warning of the FLQ's intentions to kidnap political officials before the October Crisis of 1970 had not been provided, and they were not given adequate intelligence on the nature and capabilities of the threat during the crisis. Essentially, the argument asserts that there had been a failure on the part of the intelligence-community in Canada to predict the FLQ's future act

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Walton, Brien C. "Is emotional intelligence predictive or entrepreneurial success?" Thesis, University of Pennsylvania, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10158700.

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<p> There are more self-made, billionaire entrepreneurs than billionaires who simply inherited their fortunes, but the majority of startup ventures fail within five years. A possible factor in business success or failure could be the emotional intelligence (EI) level of the entrepreneur, defined broadly as the ability to perceive, interpret, and manage emotions. Although there is substantial literature on EI applications in established organizations, there are few empirical studies exploring the predictive value of EI in the context of success for startup entrepreneurs. The purpose of this stu

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Fayad, Ramzi. "Predictive tool monitoring system for metal machining using aritificial intelligence methods." Thesis, University of Nottingham, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.433992.

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Murphy, Killian. "Predictive maintenance of network equipment using machine learning methods." Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAS013.

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Avec la montée en puissance des capacités de calcul nécessaires pour les méthodes plus développées d'Apprentissage Machine (ML), la Prédiction des Incidents Réseau (NFP:Network Fault Prediction) connait un regain d'intérêt scientifique. La capacité de prédire les incidents des équipements réseau est de plus en plus fréquemment identifiée comme un moyen efficace d'améliorer la fiabilité du réseau. Cette capacité prédictive peut être utilisée pour atténuer ou mettre en œuvre une maintenance prédictive en prévision des cas d'incidents réseau imminents. Cela pourrait contribuer à la mise en œuvre

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Espinoza, Espinoza Bertha Yrene, and Rivera Natalia Elizabeth Gutiérrez. "Sistema de información para la toma de decisiones, usando técnicas de análisis predictivo para la Empresa IASACORP International S.A." Bachelor's thesis, Universidad Ricardo Palma, 2015. http://cybertesis.urp.edu.pe/handle/urp/1271.

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En la actualidad, las empresas manejan una gran cantidad de información, el cual era inimaginable años atrás, la capacidad de recolectarla es muy impresionante. En consecuencia, para varias empresas esta información se ha convertido en un tema difícil de manejar. Diariamente, las empresas sea del sector, tipo o tamaño que sea, toman decisiones, las cuales la mayoría son decisiones estratégicas que pueden afectar el correcto funcionamiento de la empresa. Es aquí, donde ingresa una de las herramientas más mencionadas en el área de TI: Business Intelligence, este término se refiere al uso de dat

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Boots, Byron. "Spectral Approaches to Learning Predictive Representations." Research Showcase @ CMU, 2012. http://repository.cmu.edu/dissertations/131.

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A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must obtain an accurate environment model, and then plan to maximize reward. However, for complex domains, specifying a model by hand can be a time consuming process. This motivates an alternative approach: learning a model directly from observations. Unfortunately, learning algorithms often recover a model that is too inaccurate to support planning or too large and complex for planning to succeed; or, they require excessive prior domain knowledge

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Mitchell-White, Kathleen. "Reflective thinking and emotional intelligence as predictive performance factors in problem-based learning situations." ScholarWorks, 2010. https://scholarworks.waldenu.edu/dissertations/788.

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Continued improvement of the training and preparation of Federal Bureau of Investigation (FBI) special agents is critical to the organization's ability to protect the national security of the United States. Too little attention has been paid to the factors that improve new agent trainees' (NATs) ability to learn and succeed in their training programs. Based on the theories of reflective thinking and emotional intelligence, this nonexperimental, correlational study explored predictors of NATs' (N = 183) performance in problem-based exercises as part of the 20-week training program. Self-report

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Colburn, andrea Adams. "The Predictive Value of Emotional Intelligence: using Emotional Intelligence to Predict Success in and Satisfaction with Romantic and Friendship Relationships and Career." W&M ScholarWorks, 1997. https://scholarworks.wm.edu/etd/1539626138.

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Nickens, Nicole M. "Impact of intersubtest scatter on predictive validity of WISC-III /." free to MU campus, to others for purchase, 2003. http://wwwlib.umi.com/cr/mo/fullcit?p3091949.

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Zarei, Anahita. "A novel assessment index and intelligent predictive models for orthodontics /." Thesis, Connect to this title online; UW restricted, 2007. http://hdl.handle.net/1773/6093.

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Pilon, Bruno Hernandes Azenha. "Predictive analytics via gaussian processes and statistical audit via gaussian mixtures in business intelligence systems." reponame:Repositório Institucional da UnB, 2015. http://dx.doi.org/10.26512/2015.04.D.18956.

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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2015.<br>Um sistema de Inteligência de Negócios, do inglês \emph{Business Intelligence} (BI), é um sistema de informação que emprega ferramentas de diversas áreas do conhecimento na coleta, integração e análise de dados para aprimorar e embasar o processo decisório em empresas e instituições governamentais. O Ministério do Planejamento, Orçamento e Gestão (MP), órgão do governo federal brasileiro, possui uma série de sistemas de inteligência de negócios e, neste trabalho, dois destes

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Walters, Ryan L. "The Predictive Power of Machiavellianism, Emotional Manipulation, Agreeableness, and Emotional Intelligence on Counterproductive Work Behaviors." Wright State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=wright1623081304072487.

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Aronsson, Henrik. "Modeling strategies using predictive analytics : Forecasting future sales and churn management." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-167130.

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This project was carried out for a company named Attollo, a consulting firm specialized in Business Intelligence and Corporate Performance Management. The project aims to explore a new area for Attollo, predictive analytics, which is then applied to Klarna, a client of Attollo. Attollo has a partnership with IBM, which sells services for predictive analytics. The tool that this project is carried out with, is a software from IBM: SPSS Modeler. Five different examples are given of what and how the predictive work that was carried out at Klarna consisted of. From these examples, the different pr

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Ford, Leif Allen. "Predictive Ability of Emotional Intelligence Scores on Employee Self-Reported Perception of Comprehensive Organizational Credibility Inventory." ScholarWorks, 2016. https://scholarworks.waldenu.edu/dissertations/2285.

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Research has shown that emotional intelligence (EQ) is positively related to beneficial outcomes in organizations. Research has also found that negative perceptions of organizational credibility (OC) can result in adverse economic and social costs for organizations and communities. To date, the existing research has failed to examine whether employee EQ might affect employee perceptions of OC. A quantitative, non-experimental study was conducted using a sample of employees in large health and medical organizations throughout the United States. The variables in the study were measured using the

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Legkiy, Yaroslav, Ярослав Ярославович Легкий, Bohdan Dubchak, and Богдан Мстиславович Дубчак. "Machine learning &artificial intelligence in aerospace industry." Thesis, National Aviation University, 2021. https://er.nau.edu.ua/handle/NAU/50479.

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Machine Learning & Artificial Intelligence in Aerospace Industry URL: https://www.axiscades.com/blog-resources/whitepaper/Aerospacewhitepaper.pdf<br>It depicts the artіficіal іntelligence as a signіficant role іn cutting costs, reducing the design cycle tіme, simulation, prototyping, optimizatіon, maіntenance, manufacturіng and updatіng products.<br>Визначено штучний інтелект як значущу роль у скороченні витрат, зменшенні часу циклу проектування, моделюванні, прототипуванні, оптимізації, технічному обслуговуванні, виробництві та модернізації продукції.

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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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Verenich, Ilya. "Explainable predictive monitoring of temporal measures of business processes." Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/124037/1/Ilya_Verenich_Thesis.pdf.

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This thesis explores data-driven, predictive approaches to monitor business process performance. These approaches allow process stakeholders to prevent or mitigate potential performance issues or compliance violations in real time, as early as possible. To help users understand the rationale for the predictions and build trust in them, the thesis proposes two techniques for explainable predictive process monitoring: one based on deep learning, the other driven by process models. This is achieved by decomposing a prediction into its elementary components. The techniques are compared against sta

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Islam, Md Samsul, Lin Zhou, and Fei Li. "Application of Artificial Intelligence (Artificial Neural Network) to Assess Credit Risk : A Predictive Model For Credit Card Scoring." Thesis, Blekinge Tekniska Högskola, Sektionen för management, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2099.

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Credit Decisions are extremely vital for any type of financial institution because it can stimulate huge financial losses generated from defaulters. A number of banks use judgmental decisions, means credit analysts go through every application separately and other banks use credit scoring system or combination of both. Credit scoring system uses many types of statistical models. But recently, professionals started looking for alternative algorithms that can provide better accuracy regarding classification. Neural network can be a suitable alternative. It is apparent from the classification out

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He, Bin. "A Machine Learning Approach for Data Unification and Its Application in Asset Performance Management." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/79141.

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The amount of data is growing fast with the advance of data capturing and management technologies. However, data from different source are often isolated and not ready to be analyzed together as one data set. The effort of connecting pieces of isolated data into a unified data set is time consuming and often costly in terms of cognitive load and programming time. To address this problem, here we proposed an approach using machine learning to augment human intelligence in the data unification process, especially complex categorical data value unification. Many aspects of useful information are

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Osman, Norhaslinda Yasmin, and n/a. "The development of a predictive damage condition model of light structures on expansive soils using hybrid artificial intelligence techniques." Swinburne University of Technology, 2007. http://adt.lib.swin.edu.au./public/adt-VSWT20071002.131831.

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Expansive soils have damage light structures due to movement of soil which was a common problem all around the world. Soils exhibiting expansive properties were common throughout Australia. The damage to light structures founded on expansive soils in Victoria occurred mainly in properties built on quaternary basaltic clays and Tertiary to Ordovician clays. A review of existing literature in the area of expansive soils showed a lack of a thorough scientific diagnostic of the damage to light structures founded on expansive soils. Very few studies had been performed on damage to light structures

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Kantedal, Simon. "Evaluating Segmentation of MR Volumes Using Predictive Models and Machine Learning." Thesis, Linköpings universitet, Institutionen för medicinsk teknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-171102.

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A reliable evaluation system is essential for every automatic process. While techniques for automatic segmentation of images have been extensively researched in recent years, evaluation of the same has not received an equal amount of attention. Amra Medical AB has developed a system for automatic segmentation of magnetic resonance (MR) images of human bodies using an atlas-based approach. Through their software, Amra is able to derive body composition measurements, such as muscle and fat volumes, from the segmented MR images. As of now, the automatic segmentations are quality controlled by cli

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Osman, Norhaslinda Yasmin. "The development of a predictive damage condition model of light structures on expansive soils using hybrid artificial intelligence techniques." Australasian Digital Thesis Program, 2007. http://adt.lib.swin.edu.au/public/adt-VSWT20070731.124824/index.html.

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Thesis (PhD) - Swinburne University of Technology, Faculty of Engineering and Industrial Sciences, 2007.<br>Submitted in fulfilment of requirements for the degree of Doctor of Philosophy, Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, 2007. Typescript. Includes bibliographical references (p. 174-202).

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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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BERNARDINI, MICHELE. "Machine Learning approaches in Predictive Medicine using Electronic Health Records data." Doctoral thesis, Università Politecnica delle Marche, 2021. http://hdl.handle.net/11566/289622.

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L' approccio tradizionale in medicina per gestire le patologie può essere ridotto al concetto di “one-size-fits all”, in cui l'effetto di una cura rispecchia l'intero campione. Però, la medicina di precisione può rappresentare l'estensione e l'evoluzione della medicina tradizionale perché risulta principalmente preventiva e proattiva piuttosto che prettamente reattiva. Questa evoluzione può portare a una Sanità predittiva, personalizzata, preventiva, partecipativa e psicocognitiva. Tra tutte queste caratteristiche, la tesi si focalizza sulla medicina predittiva. Quindi, si può introdurre un n

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Moyer, Adam C. "Self-Evolving Data Collection Through Analytics and Business Intelligence to Predict the Price of Cryptocurrency." Ohio University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1604656483616404.

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Legha, Daniel. "Predictive maintenance and remote diagnosis for electro-mechanical drives of Very High Speed Trains." Electronic Thesis or Diss., La Rochelle, 2023. http://www.theses.fr/2023LAROS015.

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L'objectif principal de cette recherche est de mettre en œuvre des méthodes de diagnostic prédictif et à distance pour les systèmes d'accessibilité du train, qui sont entraînés par des moteurs à courant continu. Ces systèmes sont les suivants : Les portes intérieures, le gap filler, la porte d'accès des passagers et l'ascenseur. La recherche aborde de multiples équations de maintenance prédictive et de télédiagnostic, telles que : Test de la tension de la courroie, pour tous les types de portes intérieures. Le bon état de la butée d'ouverture de la porte, pour tous les types de portes intérieu

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Zhou, Gordon. "Machine Learning-Based Cost Predictive Model for Better Operating Expenditure Estimations of U.S. Light Rail Transit Projects." Thesis, The George Washington University, 2021. http://pqdtopen.proquest.com/#viewpdf?dispub=28157527.

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Inaccurate forecasts of operating expenditures during the planning phase for new Light Rail Transit (LRT) projects in the United States underestimated future costs by up to 45% (Pickrell, 1989). When operating expenditures exceeded projected levels, local transit agencies often reduced public transit services to operate within their respective annual budgets. Therefore, it is imperative for transit agencies to produce reasonably accurate planning estimates to secure sufficient funding to support future operations, maintenance, and service delivery associated with LRT systems. The research aime

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Nitz, Pettersson Hannes, and Samuel Vikström. "VISION-BASED ROBOT CONTROLLER FOR HUMAN-ROBOT INTERACTION USING PREDICTIVE ALGORITHMS." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-54609.

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The demand for robots to work in environments together with humans is growing. This calls for new requirements on robots systems, such as the need to be perceived as responsive and accurate in human interactions. This thesis explores the possibility of using AI methods to predict the movement of a human and evaluating if that information can assist a robot with human interactions. The AI methods that were used is a Long Short Term Memory(LSTM) network and an artificial neural network(ANN). Both networks were trained on data from a motion capture dataset and on four different prediction times:

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Lawlor, Mary Ann C. "Predictors of Health Service Use in Persons with Heart Failure." Case Western Reserve University School of Graduate Studies / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=case1619702345236178.

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Malazizi, Ladan. "Development of Artificial Intelligence-based In-Silico Toxicity Models. Data Quality Analysis and Model Performance Enhancement through Data Generation." Thesis, University of Bradford, 2008. http://hdl.handle.net/10454/4262.

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Toxic compounds, such as pesticides, are routinely tested against a range of aquatic, avian and mammalian species as part of the registration process. The need for reducing dependence on animal testing has led to an increasing interest in alternative methods such as in silico modelling. The QSAR (Quantitative Structure Activity Relationship)-based models are already in use for predicting physicochemical properties, environmental fate, eco-toxicological effects, and specific biological endpoints for a wide range of chemicals. Data plays an important role in modelling QSARs and also in result an

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Klaesson, Mårten. "Exploring factors that decides on how a Business Intelligence tool is being received by its users." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-417292.

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Self-Service Business Intelligence (SSBI) is a service where users can create reports andanalyze data on their own. It is an approach to decentralize competence and knowledge withina company. It has been proven to increase productivity and provide employees with morepossibilities to make smart data-driven decisions. I decided to do this project to learn moreabout SSBI and specifically explore what factors that contributes to the user experience ofworking with SSBI. With the help of a survey I was able to reach out to the employees at IfP&C Insurance.I asked how satisfied they were with the

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Shewinvanakitkul, Prapan. "Automated Detection and Prediction of Sleep Apnea Events." Case Western Reserve University School of Graduate Studies / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1486490112558014.

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Chang, Acer Yu-Chan. "The role of predictive processing in conscious access and regularity learning across sensory domains." Thesis, University of Sussex, 2017. http://sro.sussex.ac.uk/id/eprint/70234/.

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To increase fitness for survival, organisms not only passively react to environmental changes but also actively predict future events to prepare for potential hazards within their environment. Accumulating evidence indicates that the human brain is a remarkable predictive machine which constantly models causal relationships and predicts future events. This ‘predictive processing' framework, a prediction-based form of Bayesian inference, states that the brain continuously generates and updates predictions about incoming sensory signals. This framework has been showing notable explanatory power

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Wang, Xiangxue. "A PROGNOSTIC AND PREDICTIVE COMPUTATIONAL PATHOLOGY BASED COMPANION DIAGNOSTIC APPROACH: PRECISION MEDICINE FOR LUNG CANCER." Case Western Reserve University School of Graduate Studies / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1574125440501667.

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Papineau, Christelle. "Droit et intelligence artificielle : essai pour la reconnaissance du droit computationnel." Thesis, Paris 1, 2019. http://www.theses.fr/2019PA01D049.

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La porosité entre le droit et l’intelligence artificielle a aujourd’hui soixante ans. Cette porosité qui devait, à l’origine, permettre aux informaticiens d’améliorer les performances cognitives de leurs algorithmes, ce, grâce au syllogisme juridique, a très vite suscité, en retour, l’intérêt des juristes pour l’informatique. Ces derniers ont compris qu’ils pouvaient tirer avantage des opportunités offertes par l’automatisation du droit, grâce aux nouvelles technologies. Ainsi, à l’aube de la décennie 2020, le machine learning, l’un des sous champ disciplinaires les plus récents de l’intellige

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Alaya, Mili Nourhene. "Managing the empirical hardness of the ontology reasoning using the predictive modelling." Thesis, Paris 8, 2016. http://www.theses.fr/2016PA080062/document.

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Multiples techniques d'optimisation ont été implémentées afin de surmonter le compromis entre la complexité des algorithmes du raisonnement et l'expressivité du langage de formulation des ontologies. Cependant les compagnes d'évaluation des raisonneurs continuent de confirmer l'aspect imprévisible et aléatoire des performances de ces logiciels à l'égard des ontologies issues du monde réel. Partant de ces observations, l'objectif principal de cette thèse est d'assurer une meilleure compréhension du comportement empirique des raisonneurs en fouillant davantage le contenu des ontologies. Nous avo

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Merabet, Samir. "Vers un droit de l'intelligence artificielle." Thesis, Aix-Marseille, 2018. http://www.theses.fr/2018AIXM0528.

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Récente dans l’histoire des inventions technologiques, l’intelligence artificielle s’est néanmoins rapidement imposée dans la société, bouleversant à cette occasion l’économie comme le marché de l’emploi. Toutes les professions semblent exposées à la concurrence des agents artificiels ; rares sont les domaines d’activités épargnés. Pourtant, il apparaît que ces deux formes d’intelligences ne peuvent pas être tenues pour équivalentes. Si l’intelligence artificielle emprunte certains aspects de l’intelligence humaine, de nombreux autres lui font défaut. La conscience, la raison comme les émotion

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Merabet, Samir. "Vers un droit de l'intelligence artificielle." Electronic Thesis or Diss., Aix-Marseille, 2018. https://buadistant.univ-angers.fr/login?url=https://bibliotheque.lefebvre-dalloz.fr/secure/isbn/9782247201235.

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Récente dans l’histoire des inventions technologiques, l’intelligence artificielle s’est néanmoins rapidement imposée dans la société, bouleversant à cette occasion l’économie comme le marché de l’emploi. Toutes les professions semblent exposées à la concurrence des agents artificiels ; rares sont les domaines d’activités épargnés. Pourtant, il apparaît que ces deux formes d’intelligences ne peuvent pas être tenues pour équivalentes. Si l’intelligence artificielle emprunte certains aspects de l’intelligence humaine, de nombreux autres lui font défaut. La conscience, la raison comme les émotion

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SABBATINI, LUISIANA. "Artificial Intelligence and Internet of Things for Industry 4.0 and Society 5.0: Exploration of Theories and Practices to Implement the Future." Doctoral thesis, Università Politecnica delle Marche, 2022. http://hdl.handle.net/11566/295522.

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Il contesto sociale di oggi è modellato da due tendenze coesistenti: spinta tecnologica e richiesta di applicazioni. Con il primo termine si intende l'emergere, la rapida evoluzione e l'applicazione di tecnologie innovative, del regno dell'ICT (come IoT) e dell'analisi dei dati (come Intelligenza Artificiale, Machine e Deep Learning). La seconda tendenza è invece una peculiarità del mercato odierno, costruito su requisiti come il basso costo, l’alto tasso tecnologico, la personalizzazione e la facile accessibilità tra gli altri. Grazie a queste due tendenze coesistenti e sinergiche, l'intera s

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Bussola, Nicole. "AI for Omics and Imaging Models in Precision Medicine and Toxicology." Doctoral thesis, Università degli studi di Trento, 2022. http://hdl.handle.net/11572/348706.

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This thesis develops an Artificial Intelligence (AI) approach intended for accurate patient stratification and precise diagnostics/prognostics in clinical and preclinical applications. The rapid advance in high throughput technologies and bioinformatics tools is still far from linking precisely the genome-phenotype interactions with the biological mechanisms that underlie pathophysiological conditions. In practice, the incomplete knowledge on individual heterogeneity in complex diseases keeps forcing clinicians to settle for surrogate endpoints and therapies based on a generic one-size-fits-al

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Diaz, Mantilla Francisco Alberto, and Hidalgo Alexander Ocampo. "Desarrollo de un APP basado en modelos predictivos y tecnología GPS para la recomendación y reservas de espacios en playas de estacionamiento." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2021. http://hdl.handle.net/10757/657317.

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El presente proyecto de tesis reúne la información del proceso y los sub procesos involucrados en la gestión de venta de eventuales Central Parking Systems S.A., así mismo, las nuevas ideas propuestas para la mejora de los procesos en el campo de Acción. En el capítulo 1, se expondrá el marco teórico el cual estará constituido por los fundamentos teóricos del negocio y las tendencias y tecnologías actuales, también se presentará a la organización, su estructura organizacional, sus objetivos estratégicos y sus procesos. Para cerrar el capítulo 1 se expondrá su problemática. En el capítulo

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NETO, OMAR PARANAIBA VILELA. "DESIGN, OPTIMIZATION, SIMULATION AND PREDICTION OF NANOSTRUCTURES PROPERTIES BY COMPUTATIONAL INTELLIGENCE TECHNIQUES: INTELLIGENT COMPUTATIONAL NANOTECHNOLOGY." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2009. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=15182@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>FUNDAÇÃO DE APOIO À PESQUISA DO ESTADO DO RIO DE JANEIRO<br>Esta tese investiga a Nanotecnologia Computacional Inteligente, isto é, o apoio de técnicas de Inteligência Computacional (IC) nos desafios enfrentados pela Nanociência e Nanotecnologia. Por exemplo, utilizam-se as Redes Neurais para construir sistemas de inferência capazes de relacionar um conjunto de parâmetros de entrada com as características finais das nanoestruturas, permitindo aos pesquisadores prever o comport

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Soualhi, Abdenour. "Du diagnostic au pronostic de pannes des entraînements électriques." Thesis, Lyon 1, 2013. http://www.theses.fr/2013LYO10146/document.

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Le diagnostic et le pronostic de pannes des systèmes d'entraînement électriques est un enjeu majeur pour assurer la fiabilité et la sûreté de fonctionnement des outils de production notamment dans les secteurs sensibles (militaire, l'aéronautique, l'aérospatiale et nucléaire, etc.). Le travail de recherche présenté dans cette thèse vise à introduire de nouvelles méthodes de diagnostic et de pronostic des défauts d'une machine asynchrone ainsi que des roulements à rouleaux. Ces méthodes, orientées données, utilisent les données de mesure recueillies à partir de capteurs placés sur un système (m

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Lehnert, Christopher. "Locally weighted learning methods for non-rigid robot control." Thesis, Queensland University of Technology, 2015. https://eprints.qut.edu.au/82358/1/Christopher_Lehnert_Thesis.pdf.

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This thesis develops a novel approach to robot control that learns to account for a robot's dynamic complexities while executing various control tasks using inspiration from biological sensorimotor control and machine learning. A robot that can learn its own control system can account for complex situations and adapt to changes in control conditions to maximise its performance and reliability in the real world. This research has developed two novel learning methods, with the aim of solving issues with learning control of non-rigid robots that incorporate additional dynamic complexities. The ne

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Sawaya, Antonio. "Financial time series analysis : Chaos and neurodynamics approach." Thesis, Högskolan Dalarna, Datateknik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:du-4810.

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This work aims at combining the Chaos theory postulates and Artificial Neural Networks classification and predictive capability, in the field of financial time series prediction. Chaos theory, provides valuable qualitative and quantitative tools to decide on the predictability of a chaotic system. Quantitative measurements based on Chaos theory, are used, to decide a-priori whether a time series, or a portion of a time series is predictable, while Chaos theory based qualitative tools are used to provide further observations and analysis on the predictability, in cases where measurements provid

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Boza, Condorena Edwin Guido 1958. "Identificação de processos e controle preditivo com modelo utilizando técnicas de inteligência artificial aplicadas à produção de bioetanol." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/266648.

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Orientador: Aline Carvalho da Costa<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Química<br>Made available in DSpace on 2018-08-21T12:53:49Z (GMT). No. of bitstreams: 1 BozaCondorena_EdwinGuido_D.pdf: 5093932 bytes, checksum: 505cbc2b6c875e35004ad875c0f0ac6a (MD5) Previous issue date: 2012<br>Resumo: Na presente tese foram abordados problemas no contexto da produção de etanol de primeira e segunda geração. No caso de etanol de segunda geração foi abordado o problema de melhorar a eficiência da hidrolise enzimática, com as seguintes contribuições: (1) otimi

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Lieti, Valerio. "Development of an Industrial IoT End-to-End Use Case." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

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This project is born merging my personal interest in IoT and AI fields and the collaboration with WiLab, Bi-rex and EBWorld. By joining different skills, the final result is the realization of an end-to-end Industrial IoT application. This IIoT use-case focuses on monitoring accelerations that characterize a turntable, on which mechanical parts are processed. The purpose of the monitoring is to implement predictive maintenance to report potential malfunctions. The turntable in question belongs to DMG Mori, a five-axis turning and milling machine for subtractive manufacturing, machine located a

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Joorabchi, Amirhassan. "Intelligent Predictive Models for Water resources Engineering." Thesis, Griffith University, 2009. http://hdl.handle.net/10072/367450.

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Fresh water is considered to be one of the most important resources for humans and the environment. Due to the increase in population and the currently unsustainable usage of this limited resource, more attention is needed in the management of water resources. Advanced computational methods can help in attaining a better understanding of all aspects of water. Indeed, a better understanding of water resources requires a vast knowledge of a wide variety of fields such as atmospheric science, geology, hydrology, hydraulics and mathematics etc. To assist in this process computing techniques have b

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Jones, Malachi G. "Asymmetric information games and cyber security." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50284.

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A cyber-security problem is a conflict-resolution scenario that typically consists of a security system and at least two decision makers (e.g. attacker and defender) that can each have competing objectives. In this thesis, we are interested in cyber-security problems where one decision maker has superior or better information. Game theory is a well-established mathematical tool that can be used to analyze such problems and will be our tool of choice. In particular, we will formulate cyber-security problems as stochastic games with asymmetric information, where game-theoretic methods can then

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Lewis, Howard. "Intelligent monitoring and prediction systems." Thesis, University of Liverpool, 2000. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.399092.

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