Titlebook: Soft Computing for Recognition based on Biometrics; Patricia Melin,Janusz Kacprzyk,Witold Pedrycz Book 2010 Springer Berlin Heidelberg 201

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Application of the Bee Swarm Optimization BSO to the Knapsack Problemalgorithms which are inspired from intelligent behavior of honey bees are among the most recently introduced population based techniques. In this paper, a novel hybrid algorithm based in Bees Algorithm and Particle Swarm Optimization is applied to the Knapsack Problem. The Bee Algorithm is a new pop

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An Approach Based on Neural Networks for Gas Lift Optimizationtion system. Two cases are analyzed: a) A single well production system and b) A production system composed by two gas lifted wells. For both cases minimizing the objective function of the proposed strategy shows the ability of the neural networks to approximate the behavior of an oil production sys

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A New Evolutionary Method with Particle Swarm Optimization and Genetic Algorithms Using Fuzzy Systemhms (GAs) using Fuzzy Logic for parameter adaptation and integrate the results. The new evolutionary method combines the advantages of PSO and GA to give us an improved FPSO+FGA hybrid method. Fuzzy Logic is used to combine the results of the PSO and GA in the best way possible. The new hybrid FPSO+

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Local Survival Rule for Steer an Adaptive Ant-Colony Algorithm in Complex Systemsstems is the search mechanism. The unstructured nature of real-world large-scale complex systems poses a challenge to the search methods, becasuse global routing and directory services are impractical to implement. In this paper, a new ant-colony algorithm, Adaptive Neighboring-Ant Search (AdaNAS),

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Comparative Study of Type-2 Fuzzy Inference System Optimization Based on the Uncertainty of Membersh to test the optimization method for the fuzzy systems. First, we tested the methodology by manually incrementing the percentage in the FOU, later we apply a Genetic Algorithm to find the optimal type-2 fuzzy system. We show the comparative results obtained for the benchmark problems.

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Modular Neural Networks for Person Recognition Using the Contour Segmentation of the Human Iris Biomned to make a cut of the area of interest by removing the noise around the iris. The input to the modular neural networks are the processed iris images and the output is the number of the person identified. The integration of the modules was done with a gating network method.

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1860-949X is book, bio-inspired models and applications of hybrid intel- gent systems using soft computing techniques for image analysis and pattern r- ognition based on biometrics and other information sources. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, ne

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Book 2010ttern r- ognition based on biometrics and other information sources. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book i