Neuro Fuzzy Model
Mostrando 13-24 de 27 artigos, teses e dissertações.
-
13. 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
-
14. 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
-
15. 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
-
16. 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
-
17. 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
-
18. Estudo comparativo entre tecnicas de inteligencia artificial e modelos lineares em determinações quantitativas no infravermelho proximo
In this work it was done a comparative study among the performances of different artificial intelligence techniques and two multivariate linear calibration methods (Multiple Linear Regression and Partial Least Squares), in three different chemical systems for quantitative determination in the near infrared region. The artificial intelligence techniques are a
Publicado em: 2003
-
19. MODELAGEM E CONTROLE NEURO-FUZZY DE SISTEMAS DINÂMICOS / NEURO-FUZZY MODELLING AND CONTROL OF DYNAMIC SISTEMS
In this work procedures for neuro-fuzzy modelling and control of dynamic systems are reviewed and a new structure is proposed. In this, modelling and closed-loop control are performed simultaneously by using a neuro-fuzzy approach. In the modelling stage the input space of a dynamic system (plant) is initially divided into a number of fuzzy operating regions
Publicado em: 2002
-
20. HIERARCHICAL NEURO-FUZZY BSP-MAMDANI MODEL / MODELO NEURO-FUZZY HIERÁRQUICOS BSP MAMDANI
Esta dissertação investiga a utilização de sistemas Neuro- Fuzzy Hierárquicos BSP (Binary Space Partitioning) para aplicações em classificação de padrões, previsão, sistemas de controle e extração de regras fuzzy. O objetivo é criar um modelo Neuro-Fuzzy Hierárquico BSP do tipo Mamdani a partir do modelo Neuro-Fuzzy Hierárquico BSP Class (NFH
Publicado em: 2002
-
21. COMBINING NEURAL NETWORKS AND FUZZY LOGIC FOR APPLICATIONS IN CHARACTER RECOGNITION
This thesis investigates the benefits of combining neural networks and fuzzy logic into neuro-fuzzy systems, especially for applications in character recognition tasks. The research reported in this thesis is divided into two parts. In the first part, two main neurofuzzy systems are described and investigated - the fuzzy MLP and RePART models. The former is
Publicado em: 2001
-
22. UM SISTEMA DE DIAGNÓSTICO DE EQUIPAMENTOS ELÉTRICOS DE ALTA TENSÃO COM BASE NA OCORRÊNCIA DE DESCARGAS PARCIAIS / A DIAGNOSTICS SYSTEM OF HIGH VOLTAGE POWER APPARATUS BASED IN PARTIAL DISCHARGES OCURRENCE
High voltage (HV) power apparatus are fundamental parts in the industrial process. It is also well Known that electrical insulation systems are the parts that present more problems through the life cycle of an HV apparatus. The dielectric properties of materials are altered during operation time and for this reason they should be monitored. Among the main an
Publicado em: 2001
-
23. NEURO-FUZZY BSP HIERARCHICAL SYSTEM FOR TIME FORECASTING AND FUZZY RULE EXTRACTION DOR DATA MINING APPLICATONS / SISTEMA NEURO-FUZZY HIERÁRQUICO BSP PARA PREVISÃO E EXTRAÇÃO DE REGRAS FUZZY EM APLICAÇÕES DE DATA MINING
This dissertation investigates the use of a Neuro-Fuzzy Hierarchical system for time series forecasting and fuzzy rule extraction for Data Mining applications. The objective of this work was to extend the Neuro-Fuzzy BSP Hierarchical model for the classification of registers and time series forecasting. The process of classification of registers in the Data
Publicado em: 2000
-
24. ARTIFICIAL NEURAL NETWORKS, FUZZY LOGIC AND NEURO-FUZZY SYSTEM IN THE ROLE OF SHORT TERM LOAD FORECAST / REDES NEURAIS ARTIFICIAIS, LÓGICA NEBULOSA E SISTEMAS NEURO-FUZZY NA PREVISÃO DE CARGA ELÉTRICA EM CURTO PRAZO
This thesis examines the performance of computational intelligence in short term load forecasting. The main objective of the work was to propose and evaluate neural network, fuzzy logic, neurofuzzy and hybrid systems in the role of short term load forecast, considering some variables that affect the load behavior such as temperature, comfort indexes and cons
Publicado em: 1999