Neuro Fuzzy Systems
Mostrando 13-24 de 34 artigos, teses e dissertações.
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13. Controlador supervisório inteligente para sistemas híbridos eólico-diesel-bateria de pequeno porte. / An intelligent supervisory controller for wind-diesel-battery systems.
This work presents the development and simulation results of an Intelligent Supervisory Controller for hybrid power systems. The controller uses artificial intelligence techniques, based on artificial neural networks and neuro-fuzzy logic, to forecast both wind power and load, and to take optimal dispatch decisions for hybrid power systems. The main controll
Publicado em: 2007
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14. Prediction of time series using architecture based on neuro-fuzzy systems. / Predição não-linear de séries temporais usando sistemas de arquitetura neuro-fuzzy.
This master dissertation has as main objetive applies systems of neuro-fuzzy architecture for functions prediction in serie times. The architecture carried out is the Adaptive Neuro-Fuzzy Inference System (ANFIS). This architecture is a kind of Fuzzy Inference Systems (FIS) implemen- tation under a paradigm of arti¯cial neural networks. Making use of techno
Publicado em: 2006
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15. Técnicas inteligentes hídridas para o controle de sistemas não lineares
Neste trabalho é mostrado tanto o desenvolvimento quanto as características de algumas das principais técnicas utilizadas para o controle inteligente de sistemas. Partindo de um controlador fuzzy foi possível aplicar técnicas de aprendizagem, similares às utilizadas pelas Redes Neurais Artificiais (RNA s), evoluir para os modelos neuro-fuzzy ANFIS e NE
Publicado em: 2006
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16. Geostatistics and Fuzzy Systems in Plant Protection / Geostatistics and Fuzzy systems in plant protection
Em um paÃs de dimensÃes continentais como o Brasil, existe carÃncia de informaÃÃes de apoio à decisÃo sobre problemas agrÃcolas e ambientais, nos quais a GeociÃncia e InteligÃncia Artificial apresentam enorme potencial de utilizaÃÃo. Torna-se cada vez mais necessÃrio utilizar essas metodologias para otimizar recursos e reduzir custos dos program
Publicado em: 2006
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17. DATA MINING APPLIED TO CUSTOMER RETENTION IN WIRELESS TELECOMMUNICATIONS / MINERAÇÃO DE DADOS NA RETENÇÃO DE CLIENTES EM TELEFONIA CELULAR
The goal of this work is to propose a complete data mining system for the solution of customer retention problems, commonly found in many industries. Such a solution encompasses the accurate identification among huge amounts of data of those consumers who would most likely end their relationship with the firm, based on their historical behavior and individua
Publicado em: 2005
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18. IDENTIFICAÇÃO DE GRUPOS ESTRATÉGICOS: UMA ABORDAGEM UTILIZANDO A VISÃO RESOURCE-BASED E SISTEMAS NEURO-FUZZY / STRATEGIC GROUPS: ARESOURCE-BASED VIEW AND NEURO-FUZZY SYSTEMS APPROACH
Since its has introduced, in the beginning of the decade of seventy, the concept of strategic groups is object of theoretical and empirical research that aims to confirm its existence, its contribution to performance evaluation and the formulation of the strategies of the firms. This text join these research, using the Resource-Based Views framework and soft
Publicado em: 2004
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19. HIBRID NEURO-FUZZY-GENETIC SYSTEM FOR AUTOMATIC DATA MINING / SISTEMA HÍBRIDO NEURO-FUZZY-GENÉTICO PARA MINERAÇÃO AUTOMÁTICA DE DADOS
This dissertation presents the proposal and the development of a totally automatic data mining system. The main objective is to create a system that is capable of extracting obscure information from complex databases, without demanding the presence of a technical specialist to configure it. The Hierarchical Neuro-Fuzzy Binary Space Partitioning model (NFHB)
Publicado em: 2004
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20. Desenvolvimento de uma plataforma hÃbrida para descoberta de conhecimento em bases de dados
Artificial Neural Networks (ANN) have successfully been used in tasks as the mapping of complex functions and pattern recognition. This success is due to the ANN ability to make calculations of complicated and undetermined data, learn from examples, generalize the learned information, extract patterns and discover tendencies. Despite these advantages, it is
Publicado em: 2004
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21. Sistema neural hÃbrido para reconhecimento de padrÃes em um nariz artificial / Hybrid neural system forpattern recognition in an artificial nose
This dissertation investigates the use of Hybrid Intelligent Systems in the pattern recognition system of an artificial nose. The work involves five main parts: (1) an evaluation of the odors database by a multivariate statistics technique; (2) a validation of the Time Delay Neural Networks in the odors recognition; (3) an evaluation of the Wavelet Transform
Publicado em: 2004
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22. HIERARQUICAL NEURO-FUZZY MODELS BASED ON REINFORCEMENT LEARNING FOR INTELLIGENT AGENTS / NOVOS MODELOS NEURO-FUZZY HIERÁRQUICOS COM APRENDIZADO POR REFORÇO PARA AGENTES INTELIGENTES
This thesis investigates neuro-fuzzy hybrid models for automatic learning of actions taken by agents. The objective of these models is to provide an agent with intelligence, making it capable of acquiring and retaining knowledge and of reasoning (infer an action) by interacting with its environment. Learning in these models is performed by a non-supervised p
Publicado em: 2003
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23. SPOT PRICE FORECASTING IN THE ELECTRICITY MARKET / PREVISÃO DO PREÇO SPOT NO MERCADO DE ENERGIA ELÉTRICA
This thesis focuses on spot price forecasting and risk management in the Brazilian electricity industry. It is proposed a new methodology for the problem based on neuro- fuzzy systems and the dispatching and planning operation programs. The main advantage of the approach is to be able to get more informative spot price distributions than using the operation
Publicado em: 2003
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24. SISTEMAS INTELIGENTES NO ESTUDO DE PERDAS COMERCIAIS DO SETOR DE ENERGIA ELÉTRICA / INTELLIGENT SYSTEMS APPLIED TO FRAUD ANALYSIS IN THE ELECTRICAL POWER INDUSTRIES
Esta dissertação investiga uma nova metodologia, baseada em técnicas inteligentes, para a redução das perdas comerciais relativas ao fornecimento de energia elétrica. O objetivo deste trabalho é apresentar um modelo de inteligência computacional capaz de identificar irregularidades na medição de demanda e consumo de energia elétrica, considerando
Publicado em: 2003