Soft Computing
D. K. Pratihar
Soft Computing D. K. Pratihar - Delhi Narosa 2014 - 246P; 185mm x 240mm
Introduction / Optimization and Some Traditional Methods / Introduction to Genetic Algorithms / Some Specialized Genetic Algorithms / Introduction to Fuzzy Sets / Fuzzy Reasoning and Clustering / Fundamentals of Neural Networks / Some Examples of Neural Networks / Combined Genetic Algorithms: Fuzzy Logic / Combined Genetic Algorithms: Neural Networks / Combined Neural Networks: Fuzzy Logic.
This book starts with an introduction to soft computing, a family consisting of many members, namely Genetic Algorithms (GAs), Fuzzy Logic (FL), Neural Networks (NNs) and others. To realize the need for a non-traditional optimization tool like GA, one chapter is devoted to explain the principle of traditional optimization. The working cycle of a GA is explained in detail. The mechanisms of some specialized GAs are then discussed with appropriate examples. Fuzzy sets are introduced before explaining the principle of fuzzy reasoning and clustering. The fundamentals of NNs are presented, prior to the discussion on various forms of NN. The combined techniques, such as GA-FL, GA-NN, NN-FL and GA-FL-NN are explained in the last three chapters.
9788184874952
006.3 / PRA
Soft Computing D. K. Pratihar - Delhi Narosa 2014 - 246P; 185mm x 240mm
Introduction / Optimization and Some Traditional Methods / Introduction to Genetic Algorithms / Some Specialized Genetic Algorithms / Introduction to Fuzzy Sets / Fuzzy Reasoning and Clustering / Fundamentals of Neural Networks / Some Examples of Neural Networks / Combined Genetic Algorithms: Fuzzy Logic / Combined Genetic Algorithms: Neural Networks / Combined Neural Networks: Fuzzy Logic.
This book starts with an introduction to soft computing, a family consisting of many members, namely Genetic Algorithms (GAs), Fuzzy Logic (FL), Neural Networks (NNs) and others. To realize the need for a non-traditional optimization tool like GA, one chapter is devoted to explain the principle of traditional optimization. The working cycle of a GA is explained in detail. The mechanisms of some specialized GAs are then discussed with appropriate examples. Fuzzy sets are introduced before explaining the principle of fuzzy reasoning and clustering. The fundamentals of NNs are presented, prior to the discussion on various forms of NN. The combined techniques, such as GA-FL, GA-NN, NN-FL and GA-FL-NN are explained in the last three chapters.
9788184874952
006.3 / PRA