Genetic Algorithm Technique in Hybrid Intelligent Systems for Pattern Recognition
PhD Scholar, Department of Computer Science, Shri Venkatashwara University, U.P. India
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In this research paper we use combination of stochastic algorithms and hybrid intelligent systems for pattern recognition or classification. Stochastic algorithm has been used for model selection of components or classification, especially when the dimension of the patterns is high. Genetic algorithms are one of the commonly used techniques for stochastic classifiers. Hybrid Intelligent Systems (HIS) combine intelligent techniques in synergistic architectures in order to provide solutions for complex problems. These systems utilize at least two of the three techniques: fuzzy logic, genetic algorithms and neural networks. The aim of their combination is to amplify their strengths and complement their weaknesses. A good architecture for a hybrid system should match each of its tasks to the appropriate intelligent technique and provide an efficient means for their integration. However, it is not always obvious or easy to build HIS architectures that achieve the higher intelligence goal. A good architecture for a hybrid system should match each of its tasks to the appropriate intelligent technique and provide an efficient means for their integration.