Titlebook: Soft Computing for Hybrid Intelligent Systems; Oscar Castillo,Patricia Melin,Witold Pedrycz Book 2008 Springer-Verlag Berlin Heidelberg 20

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Stability on Type-1 and Type-2 Fuzzy Logic Systemsimportant mathematical complexity reduction, little mathematical knowledge of the model work, and they can obtain results from imprecise data. Broadly stated, fuzzy logic control attempts to come to terms with the informal nature of the control design process. In its most basic form, the so-called M

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Comparison between Ant Colony and Genetic Algorithms for Fuzzy System Optimizationierarchical Genetic Algorithms (HGA) and the Ant Colony Optimization (ACO), the fuzzy inference system controls a benchmark problem which is “The Ball and Beam” system, optimizing the fuzzy rules of the system. Firs, we work to optimize the FIS that is structured by two inputs (the error and the der

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Type-1 and Type-2 Fuzzy Inference Systems as Integration Methods in Modular Neural Networks for Multiometry. These methods of integration are based on type-1 and type-2 fuzzy logic. Also, the fuzzy systems are optimized with simple genetic algorithms. First, we considered the use of type-1 fuzzy logic and later the approach with type-2 fuzzy logic. The fuzzy systems were developed using genetic al

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Optimization of Modular Neural Network, Using Genetic Algorithms: The Case of Face and Voice Recognik (ANN). For that matter is used a Hierarchical Genetic Algorithm, which theorically has the capacity to bring the optimal architecture and the training result of the ANN, for a particular task; in this case the recognition of an individual is via voice and face.

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A New Biometric Recognition Technique Based on Hand Geometry and Voice Using Neural Networks and Fuz The hand geometry is given by an image of “the palm” of the hand with a 480x640 size which is preprocessed with a feature extraction that uses computer vision techniques and with certain features we recognize the individual. After that we preprocessed the image and get some variables as the fingers

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A Hybrid Model Based on a Cellular Automata and Fuzzy Logic to Simulate the Population Dynamicsputational models can be considered as new advances in science. In the present work a hybrid model has been proposed on the basis of a cellular automata and fuzzy logic to simulate, in space and time, the dynamics of a population structured by ages and where the changes in the levels of the biomass

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Soft Margin Training for Associative Memories: Application to Fault Diagnosis in Fossil Electric Powt margin training for associative memories, which is efficient when training patterns are not all linearly separable. On the basis of the soft margin algorithm used to train support vector machines, the new algorithm is developed in order to improve the obtained results via optimal training algorith