Dissertations / Theses on the topic 'Hybird Artificial intelligence'
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Liu, Ziming. "Méthodes hybrides d'intelligence artificielle pour les applications de navigation autonome." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ4004.
Autonomous driving is a challenging task that has a wide range of applications in the real world. The autonomous driving system can be used in different platforms, such as cars, drones, and robots. These autonomous systems will reduce a lot of human labor and improve the efficiency of the current transportation system. Some autonomous systems have been used in real scenarios, such as delivery robots, and service robots. In the real world, autonomous systems need to build environment representations and localize themselves to interact with the environment. There are different sensors can be used for these objectives. Among them, the camera sensor is the best choice between cost and reliability. Currently, visual autonomous driving has achieved significant improvement with deep learning. Deep learning methods have advantages for environment perception. However, they are not robust for visual localization where model-based methods have more reliable results. To utilize the advantages of both data-based and model-based methods, a hybrid visual odometry method is explored in this thesis. Firstly, efficient optimization methods are critical for both model-based and data-based methods which share the same optimization theory. Currently, most deep learning networks are still trained with inefficient first-order optimizers. Therefore, this thesis proposes to extend efficient model-based optimization methods to train deep learning networks. The Gaussian-Newton and the efficient second-order methods are applied for deep learning optimization. Secondly, the model-based visual odometry method is based on the prior depth information, the robust and accurate depth estimation is critical for the performance of visual odometry module. Based on traditional computer vision theory, stereo vision can compute the depth with the correct scale, which is more reliable than monocular solutions. However, the current two-stage 2D-3D stereo networks have the problems of depth annotations and disparity domain gap. Correspondingly, a pose-supervised stereo network and an adaptive stereo network are investigated. However, the performance of two-stage networks is limited by the quality of 2D features that build stereo-matching cost volume. Instead, a new one-stage 3D stereo network is proposed to learn features and stereo-matching implicitly in a single stage. Thirdly, to keep robust, the stereo network and the dense direct visual odometry module are combined to build a stereo hybrid dense direct visual odometry (HDVO). Dense direct visual odometry is more reliable than the feature-based method because it is optimized with global image information. The HDVO is optimized with the photometric minimization loss. However, this loss suffers noises from the occlusion area, homogeneous texture area, and dynamic objects. This thesis explores removing noisy loss values with binary masks. Moreover, to reduce the effects of dynamic objects, semantic segmentation results are used to improve these masks. Finally, to be generalized for a new data domain, a test-time training method for visual odometry is explored. These proposed methods have been evaluated on public autonomous driving benchmarks, and show state-of-the-art performances
Wen, Chien-Hsien. "Applying artificial intelligence hybrid techniques in wastewater treatment." Ohio : Ohio University, 1997. http://www.ohiolink.edu/etd/view.cgi?ohiou1184357721.
Castorina, Giovanni. "Artificial intelligence based hybrid systems for financial forecasting." Thesis, University of the West of England, Bristol, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365146.
Rodic, Daniel. "A Hybrid search heuristic-exhaustive search approach for rule extraction." Pretoria : [s.n.], 2000. http://upetd.up.ac.za/thesis/available/etd-05292006-110006/.
Natsheh, Emad Maher. "Hybrid power systems energy management based on artificial intelligence." Thesis, Manchester Metropolitan University, 2013. http://e-space.mmu.ac.uk/314015/.
Abbas, Syed Murtuza. "Advanced Hybrid Simulation Model based on Phenomenology and Artificial Intelligence." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1427963095.
Chhabra, Rupanshi. "Control Power Optimization using Artificial Intelligence for Hybrid Wing Body Aircraft." Thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/56580.
Master of Science
Schlobach, Klaus Stefan. "Knowledge discovery in hybrid knowledge representation systems." Thesis, King's College London (University of London), 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.272023.
Viademonte, da Rosa Sérgio I. (Sérgio Ivan) 1964. "A hybrid model for intelligent decision support : combining data mining and artificial neural networks." Monash University, School of Information Management and Systems, 2004. http://arrow.monash.edu.au/hdl/1959.1/5159.
Wakelam, Mark. "Intelligent hybrid approach for integrated design." Thesis, University of Nottingham, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263942.
Ortiz, Paul. "Conception d’un système hybride de stockage de l’énergie pour la réduction des émissions carbone dans l’habitat individuel." Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0208.
Private homes are increasingly fitted with PhotoVoltaics (PV) for increasing the renewable energy use. Typical issues of this type of installation are : (1) the production of green energy is not necessary in line with the inhabitants' energy consumption (2) a peak of energy demand on smart grid increases the carbon emission. Mitigating carbon emission in using efficiently PV is the main objective of this research, which is part of the INTERREG NW Europe RED WOLF project (H2020 programme). This project is led led by Leeds Beckett University and involves 21 partners across Europe, including University of Lorraine. The RED WOLF project aims at installing PV solar panels and home batteries across UK, France, Netherlands, and Ireland, with the overall goal to design a Smart Storage Driver (SDS) system capables at storing solar energy produced at home, and using it when a peak of energy demand is detected on smart grid. To this end, the research is divided into three steps: (i) first, it is necessary to understand how inhabitants behave in order to obtain an energy consumption pattern for each home. This pattern will be used to size the batteries and to smartly manage the switching between the use of local and smart grid energy. Specific instrumentation will be deployed to achieve this step ; (ii) second, it is necessary to design a SDS system aiming at analysing data coming from multiple sources (e.g., smart grid, weather, indoor temperature, inhabitant behaviour, battery charge level) with one major target : the limitation of carbon emission ; (iii) finally, a global analysis ofdata management (Cloud and Fog) and network management (SDN, IoT) must be carried out in order to find the best trade off between Quality of Service offered for inhabitants and environmental impact
Khan, Laiq. "Hybrid AI paradigms applied to power system damping controls." Thesis, University of Strathclyde, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.273412.
Benbernou, Reda. "Application of artificial intelligence to seismic horizon mapping : An integrated hybrid approach." Thesis, University of Reading, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.529953.
Akinade, Olugbenga Olawale. "BIM-based software for construction waste analytics using artificial intelligence hybrid models." Thesis, University of the West of England, Bristol, 2017. http://eprints.uwe.ac.uk/31762/.
Chaiyaratana, Nachol. "Neuro-genetic based hybrid frameworks with applications in biomedicine and robotics." Thesis, University of Sheffield, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.298963.
Rudnick, Alexander James. "Cross-Lingual Word Sense Disambiguation for Low-Resource Hybrid Machine Translation." Thesis, Indiana University, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=13422906.
This thesis argues that cross-lingual word sense disambiguation (CL-WSD) can be used to improve lexical selection for machine translation when translating from a resource-rich language into an under-resourced one, especially when relatively little bitext is available. In CL-WSD, we perform word sense disambiguation, considering the senses of a word to be its possible translations into some target language, rather than using a sense inventory developed manually by lexicographers.
Using explicitly trained classifiers that make use of source-language context and of resources for the source language can help machine translation systems make better decisions when selecting target-language words. This is especially the case when the alternative is hand-written lexical selection rules developed by researchers with linguistic knowledge of the source and target languages, but also true when lexical selection would be performed by a statistical machine translation system, when there is a relatively small amount of available target-language text for training language models.
In this work, I present the Chipa system for CL-WSD and apply it to the task of translating from Spanish to Guarani and Quechua, two indigenous languages of South America. I demonstrate several extensions to the basic Chipa system, including techniques that allow us to benefit from the wealth of available unannotated Spanish text and existing text analysis tools for Spanish, as well as approaches for learning from bitext resources that pair Spanish with languages unrelated to our intended target languages. Finally, I provide proof-of-concept integrations of Chipa with existing machine translation systems, of two completely different architectures.
Liga, Davide <1990>. "Hybrid Artificial Intelligence to Extract Patterns and Rules from Argumentative and Legal Texts." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amsdottorato.unibo.it/9996/5/Davide%20Liga%20-%20unibo.pdf.
Shadabi, Fariba. "Medical outcome prediction : a hybrid artificial neural networks approach /." Canberra, 2007. http://erl.canberra.edu.au/public/adt-AUC20070816.130444/index.html.
Thesis submitted in fulfilment of the requirements of the Degree of Doctor of Philosophy in Information Sciences and Engineering, University of Canberra, January 2007. Bibliography: leaves 110-127.
Hare, Matthew Peter. "Weaver - a hybrid artificial intelligence laboratory for modelling complex, knowledge- and data-poor domains." Thesis, University of Aberdeen, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.287609.
MAINO, CLAUDIO. "Hybrid and Electric Vehicles Optimal Design and Real-time Control based on Artificial Intelligence." Doctoral thesis, Politecnico di Torino, 2022. http://hdl.handle.net/11583/2971994.
Topalli, Ayca Kumluca. "Hybrid Learning Algorithm For Intelligent Short-term Load Forecasting." Phd thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/627505/index.pdf.
but, new methods based on artificial intelligence emerged recently in literature and started to replace the old ones in the industry. In order to follow the latest developments and to have a modern system, it is aimed to make a research on STLF in Turkey, by neural networks. For this purpose, a method is proposed to forecast Turkey&rsquo
s total electric load one day in advance. A hybrid learning scheme that combines off-line learning with real-time forecasting is developed to make use of the available past data for adapting the weights and to further adjust these connections according to the changing conditions. It is also suggested to tune the step size iteratively for better accuracy. Since a single neural network model cannot cover all load types, data are clustered due to the differences in their characteristics. Apart from this, special days are extracted from the normal training sets and handled separately. In this way, a solution is proposed for all load types, including working days, weekends and special holidays. For the selection of input parameters, a technique based on principal component analysis is suggested. A traditional ARMA model is constructed for the same data as a benchmark and results are compared. Proposed method gives lower percent errors all the time, especially for holiday loads. The average error for year 2002 data is obtained as 1.60%.
Ali, Sadaqat. "Energy management of multi-source DC microgrid systems for residential applications." Electronic Thesis or Diss., Université de Lorraine, 2023. http://www.theses.fr/2023LORR0159.
Compared to the alternating current (AC) electrical grid, the direct current (DC) electrical grid has demonstrated numerous advantages, such as its natural interface with renewable energy sources (RES), energy storage systems, and DC loads. It offers superior efficiency with fewer conversion steps, simpler control without skin effect or reactive power considerations. DC microgrids remain a relatively new technology, and their network architectures, control strategies, and stabilization techniques require significant research efforts. In this context, this thesis focuses on energy management issues in a multi-source DC electrical grid dedicated to residential applications. The DC electrical grid consists of distributed generators (solar panels), a hybrid energy storage system (HESS) with batteries and a supercapacitor (SC), and DC loads interconnected via DC/DC power converters. The primary objective of this research is to develop an advanced energy management strategy (EMS) to enhance the operational efficiency of the system while improving its reliability and sustainability. A hierarchical simulation platform of the DC electrical grid has been developed using MATLAB/Simulink. It comprises two layers with different time scales: a local control layer (time scale of a few seconds to minutes due to converter switching behavior) for controlling local components, and a system-level control layer (time scale of a few days to months with accelerated testing) for long-term validation and performance evaluation of the EMS. In the local control layer, solar panels, batteries, and the supercapacitor have been modeled and controlled separately. Various control modes, such as current control, voltage control, and maximum power point tracking (MPPT), have been implemented. A low-pass filter (LPF) has been applied to divide the total HESS power into low and high frequencies for the batteries and supercapacitor. Different LPF cutoff frequencies for power sharing have also been studied. A combined hybrid bi-level EMS and automatic sizing have been proposed and validated. It mainly covers five operational scenarios, including solar panel production reduction, load reduction, and three scenarios involving HESS control combined with supercapacitor state of charge (SOC) control retention. An objective function that considers both capital expenditure (CAPEX) and operating costs (OPEX) has been designed for EMS performance evaluation. The interaction between the HESS and EMS has been jointly studied based on an open dataset of residential electrical consumption profiles covering both summer and winter seasons. Finally, an experimental platform of a multi-source DC electrical grid has been developed to validate the EMS in real-time. It comprises four lithium-ion batteries, a supercapacitor, a programmable DC power supply, a programmable DC load, corresponding DC/DC converters, and a real-time controller (dSPACE/Microlabbox). Accelerated tests have been conducted to verify the proposed EMS in different operational scenarios by integrating real solar panels and load consumption profiles. The hierarchical simulation and experimental DC electrical grid platforms can be generally used to verify and evaluate various EMS
Gibson, Paul Martyn. "The application of hybrid neural network models to archaeofaunal ageing and interpretation." Thesis, University of York, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.296383.
Adegbindin, Moustaine Kolawole Agnide. "Control Power Optimization using Artificial Intelligence for Forward Swept Wing and Hybrid Wing Body Aircraft." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/74950.
Master of Science
Scott, Lawrence Gill. "Explanations in hybrid expert systems." Thesis, University of British Columbia, 1990. http://hdl.handle.net/2429/28741.
Science, Faculty of
Computer Science, Department of
Graduate
Pacheco, Roberto Carlos dos Santos. "A Hybrid intelligent system for diagnosing and solving financial problems." reponame:Repositório Institucional da UFSC, 1996. http://repositorio.ufsc.br/xmlui/handle/123456789/76393.
Made available in DSpace on 2012-10-16T09:55:39Z (GMT). No. of bitstreams: 1 107010.pdf: 764081 bytes, checksum: e2d86b02036f32b8786711b88ac93359 (MD5)
Dinu, Razvan. "Web Agents : towards online hybrid multi-agent systems." Thesis, Montpellier 2, 2012. http://www.theses.fr/2012MON20126/document.
Multi-agent systems have been used in a wide range of applications from computer-based simulations and mobile robots to agent-oriented programming and intelligent systems in real environments. However, the largest environment in which software agents can interact is, without any doubt, the World Wide Web and ever since its birth agents have been used in various applications such as search engines, e-commerce, and most recently the semantic web. However, agents have yet to be used on the Web in a way that leverages the full power of artificial intelligence and multi-agent systems, which have the potential of making life much easier for humans. This thesis investigates how this can be changed, and how agents can be brought to the core of the online experience in the sense that we want people to talk and interact with agents instead of "just using yet another application or website". We analyze what makes it hard to develop intelligent agents on the web and we propose a web agent model (WAM) inspired by recent results in multi-agent systems. Nowadays, a simple conceptual model is the key for widespread adoption of new technologies and this is why we have chosen the MASQ meta-model as the basis for our approach, which provides the best compromise in terms of simplicity of concepts, generality and applicability to the web. Since until now the model was introduced only in an informal way, we also provide a clear formalization of the MASQ meta-model.Next, we identify the three main challenges that need to be addressed when building web agents: integration of bodies, web semantics and user friendliness. We focus our attention on the first two and we propose a set of principles to guide the development of what we call strong web agents. Finally, we validate our proposal through the implementation of an award winning platform called Kleenk. Our work is just a step towards fulfilling the vision of having intelligent web agents mediate the interaction with the increasingly complex World Wide Web
Burdelis, Mauricio Alexandre Parente. "Ajuste de taxas de mutação e de cruzamento de algoritmos genéticos utilizando-se inferências nebulosas." Universidade de São Paulo, 2009. http://www.teses.usp.br/teses/disponiveis/3/3141/tde-14082009-180444/.
This work addressed a proposal of the application of Fuzzy Systems to adjust parameters of Genetic Algorithms, during execution time. This application attempts to improve the performance of Genetic Algorithms by diminishing, at the same time: the average number of necessary generations for a Genetic Algorithm to find the desired global optimum value, as well as diminishing the number of executions of a Genetic Algorithm that are not capable of finding the desired global optimum value even for high numbers of generations. For that purpose, the results of many experiments with Genetic Algorithms were analyzed; addressing instances of the Function Minimization and the Travelling Salesman problems, under different parameter configurations. With the results obtained from these experiments, a model was proposed, for the exchange of parameter values of Genetic Algorithms, in execution time, by using Fuzzy Systems, in order to improve the performance of the system, minimizing both of the measures previously cited.
Fialho, Álvaro Roberto Silvestre. "Exploração de relações entre as técnicas nebulosas e evolutivas da inteligência computacional." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/3/3141/tde-26072007-173902/.
This work addressed a search of relations, rules and transformations between two Computational Intelligence constituent methodologies - Fuzzy Computing and Evolutionary Computing. The existence of these relations changes the actual way of solutions modeling that uses these methodologies, allowing the utilization of well established theories and models of one technique by the other in a more robust, intrinsic and transparent way. Besides the research and systematization of points that indicate the existence of relations between the two methodologies, a model to guide these exploration was proposed. By this model analysis and by the bibliographic revision made, punctual transformations were pointed out, and further consolidated through practical experiments: a Knowledge Base (KB) of a Fuzzy Logic Controller was created and modified automatically by a Genetic Algorithm. With the developed approach, besides the creation of KBs, it became possible to automatically insert new \"desired behaviors\" to existent KBs. The results of such experiments, realized through a computational platform specified and implemented to this task, were presented and analyzed.
Bontorin, alves Guilherme. "Intelligent multielectrode arrays : improving spatiotemporal performances in hybrid (living-artificial), real-time, closed-loop systems." Thesis, Bordeaux 1, 2010. http://www.theses.fr/2010BOR14056/document.
This thesis presents a promising new bioelectronics system, the Hynet. The Hynet is a Hybrid (living-artificial) Network, developed to study the long-term behavior of electrogenic cells (such as Neurons or Beta-cells), both individually and in a network. It is based on real-time closed-loop communication between a cell culture (bioware) and an artificial processing unit (hardware and software). In the first version of our Hynet, we use commercial Multielectrode Arrays (MEA) that limits its spatiotemporal performances. A new Intelligent Multielectrode Array (iMEA) is therefore developed. This new analog/mixed integrated circuit provides a large-scale, high-density, and adaptive interface with the Bioware, which improves the real-time data processing and the low-noise acquisition of the extracellular signal
Esta dissertação de doutorado apresenta um sistema bioeletrônico auspicioso, o Hynet. Esta Rede Híbrida (viva e artificial), é concebida para o estudo do comportamento à longo prazo de células eletrogeneradoras (como neurônios ou células beta), em dois aspectos : individual e em redes. Ele é baseado na comunicação bidirecional, em laço fechado e em tempo real entre uma cultura celular (Bioware) e uma unidade artificial (Hardware ou Software). Um primeiro Hynet é apresentado, mas o uso de Matrizes de Eletrodos (MEA) comerciais limita a performance do sistema. Finalmente, uma nova Matriz de Eletrodos Inteligente (iMEA) é desenvolvida. Este novo circuito integrado fornece uma interface adaptativa, em alta densidade e grande escala, com o Bioware. O novo sistema melhora o processamento de dados em tempo real e a aquisição baixo ruído do sinal extracelular
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.
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.
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).
Barla-Szabo, Daniel. "A study of gradient based particle swarm optimisers." Diss., University of Pretoria, 2010. http://hdl.handle.net/2263/29927.
Dissertation (MSc)--University of Pretoria, 2010.
Computer Science
unrestricted
Ostheimer, Julia. "Human-in-the-loop Computing : Design Principles for Machine Learning Algorithms of Hybrid Intelligence." Thesis, Linnéuniversitetet, Institutionen för informatik (IK), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-94051.
Wong, Yin-cheung Eugene, and 黃彥璋. "A hybrid evolutionary algorithm for optimization of maritime logisticsoperations." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B44526763.
Pimentel, Noeli Antônia. "SISTEMA TUTOR INTELIGENTE HÍBRIDO COM PERSONALIZAÇÃO ESTRUTURADA PELO MÉTODO DAS DIFERENÇAS FINITAS." Pontifícia Universidade Católica de Goiás, 2013. http://localhost:8080/tede/handle/tede/2446.
The generation of a pattern of navigation in Virtual Learning Environments (VLE) closer to the characteristics of the student is a question relevant of research. This paper takes as its starting point a Hybrid Intelligent Tutoring System (HITS) already proposed in the literature that uses the Artificial Neural Networks MLP (Multi Layer Perceptron) and rules of faculty experts, and adds a methodology using Partial Differential Equations (PDE) calculated by the method of finite differences, in order to improve the navigation decision to lead the student in a personalized way, adding to their biggest gains learning process. The original HITS developed for web platform has been adapted using technologies that enable the evolution system and the integration of the system settings for navigation mid-level, system without adaptive capacity, and the smart navigation were conducted to verify the effectiveness of the proposed system. Data obtained were evaluated by statistical tests with 5% level of significance, which proved the efficiency of the proposed model.
A geração de um padrão de navegação em Ambientes Virtuais de Aprendizagem (AVA) mais próximo das características do estudante é uma questão relevante de pesquisa. Esta dissertação toma como ponto de partida um Sistema Tutor Inteligente (STI) Híbrido já proposto na literatura que utiliza Redes Neurais Artificiais do tipo MLP (Multi Layer Perceptron) e regras de docentes especialistas; e agrega uma metodologia utilizando Equações Diferenciais Parciais (EDP) calculadas pelo método das diferenças finitas, com o objetivo de melhorar a decisão de navegação, para conduzir o estudante de forma personalizada, agregando melhores ganhos ao seu processo de aprendizado. O STI original, desenvolvido para plataforma web, foi adaptado utilizando tecnologias que possibilitem a evolução do sistema e a integração a Ambientes Virtuais de Aprendizagem, como o Moodle, por exemplo. Experimentos com o sistema em configurações para a navegação nível médio (sistema sem capacidade adaptativa) e a navegação inteligente foram realizados para verificação da efetividade do sistema proposto. Os dados obtidos foram avaliados por meio de testes estatísticos com nível de significância de 5%, que comprovam a eficiência do modelo proposto.
Sieberg, Philipp Maximilian [Verfasser], and Dieter [Akademischer Betreuer] Schramm. "Hybrid Methods in Vehicle Dynamics State Estimation and Control – Exploiting Potentials and Ensuring Reliability of Artificial Intelligence / Philipp Maximilian Sieberg ; Betreuer: Dieter Schramm." Duisburg, 2021. http://d-nb.info/1236501829/34.
Thorstensen, Evgenij. "Hybrid tractability of constraint satisfaction problems with global constraints." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:05707b54-69e3-40eb-97e7-63b1a178c701.
Ma, Tan. "Hybrid Power System Intelligent Operation and Protection Involving Plug-in Electric Vehicles." FIU Digital Commons, 2015. http://digitalcommons.fiu.edu/etd/1760.
Hula, Tomáš. "Experimenty s rojovou inteligencí (swarm intelligence)." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2008. http://www.nusl.cz/ntk/nusl-235936.
MERCORIO, FABIO. "Model Checking for the Analysis and Control of Complex and Non-deterministic Systems." Doctoral thesis, Università Degli Studi di L'Aquila, 2012. http://hdl.handle.net/10281/36432.
Cheng, Iunniang. "Hybrid Methods for Feature Selection." TopSCHOLAR®, 2013. http://digitalcommons.wku.edu/theses/1244.
Baumgartner, Dustin. "Global-Local Hybrid Classification Ensembles: Robust Performance with a Reduced Complexity." Connect to full text in OhioLINK ETD Center, 2009. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=toledo1241034194.
Typescript. "Submitted as partial fulfillment of the requirements for The Master of Science in Engineering." "A thesis entitled"--at head of title. Bibliography: leaves 158-164.
Fetter, Karl Christian. "Natural Selection For Disease Resistance In Hybrid Poplars Targets Stomatal Patterning Traits And Regulatory Genes." ScholarWorks @ UVM, 2019. https://scholarworks.uvm.edu/graddis/1162.
Salamon, András Z. "Transformations of representation in constraint satisfaction." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:5d641fff-4d95-43b2-9ff8-73395d782ad8.
Osório, Fernando Santos. "Inss : un système hybride neuro-symbolique pour l'apprentissage automatique constructif." Grenoble INPG, 1998. https://tel.archives-ouvertes.fr/tel-00004899.
Various Artificial Intelligence methods have been developed to reproduce intelligent human behaviour. These methods allow to reproduce some human reasoning process using the available knowledge. Each method has its advantages, but also some drawbacks. Hybrid systems combine different approaches in order to take advantage of their respective strengths. These hybrid intelligent systems also present the ability to acquire new knowledge from different sources and so to improve their application performance. This thesis presents our research in the field of hybrid neuro-symbolic systems, and in particular the study of machine learning tools used for constructive knowledge acquisition. We are interested in the automatic acquisition of theoretical knowledge (rules) and empirical knowledge (examples). We present a new hybrid system we implemented: INSS - Incremental Neuro-Symbolic System. This system allows knowledge transfer from the symbolic module to the connectionist module (Artificial Neural Network - ANN), through symbolic rule compilation into an ANN. We can refine the initial ANN knowledge through neural learning using a set of examples. The incremental ANN learning method used, the Cascade-Correlation algorithm, allows us to change or to add new knowledge to the network. Then, the system can also extract modified (or new) symbolic rules from the ANN and validate them. INSS is a hybrid machine learning system that implements a constructive knowledge acquisition method. We conclude by showing the results we obtained with this system in different application domains: ANN artificial problems(The Monk's Problems), computer aided medical diagnosis (Toxic Comas), a cognitive modelling task (The Balance Scale Problem) and autonomous robot control. The results we obtained show the improved performance of INSS and its advantages over others hybrid neuro-symbolic systems
Alsalama, Ahmed. "A Hybrid Recommendation System Based on Association Rules." TopSCHOLAR®, 2013. http://digitalcommons.wku.edu/theses/1250.
ISAKSSON, LARS JOHANNES. "HYBRID DEEP LEARNING AND RADIOMICS MODELS FOR ASSESSMENT OF CLINICALLY RELEVANT PROSTATE CANCER." Doctoral thesis, Università degli Studi di Milano, 2022. https://hdl.handle.net/2434/946529.
Leite, Patrícia Teixeira. "Aplicação de técnicas de inteligência artificial no planejamento da operação de sistemas hidrotérmicos de potência." Universidade de São Paulo, 2003. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-23042015-084714/.
The present thesis investigates a new model based on artificial inteligence as a tool to solve the problem of the operational planning of hydrothermal systems. This approach, which uses the principle of genetic evolution, has been very successful and efficient in the solution of optimization problems. To represent all the characteristics of the problem some adaptations of the traditional genetic operators of recombination and mutation were made. The problem used a string of real numbers instead of binary as usually presented in the literature. Thus, several tests were performed in order to adapt the technique to the problem, taking into account its specific characteristics. The proposed algorithm has been applied in several tests in real hydrothermal systems, with plants belonging to the brazilian southeast system. The results achieved so far have indicated that the proposed approach can be an effective alternative or a complementary technique for the planning of hidrothermal system, as it determines an operation strategy for each power plant and minimizes the expected value of the operative cost along the planning horizon. The applications include large systems, with up to 35 hydroelectric plants, where good results were obtained.
Green, Robert C. II. "Novel Computational Methods for the Reliability Evaluation of Composite Power Systems using Computational Intelligence and High Performance Computing Techniques." University of Toledo / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1338894641.