000			01845nam a22001577a 4500
005			20241023143834.0
008			241023b |||||||| |||| 00| 0 eng d
020			_a9788184877991
082			_a006.3 _bPRA
100			_aPratihar, K. Dilip
245			_aSoft computing and AI Fundamentals and Applications _cDilip K. Pratihar
260			_bNarosa _c2025
300			_a288
520			_aSoft Computing starts with an introduction to soft computing, a family consists 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 some appropriate examples. The working principles of some other non-traditional optimization tools like simulated annealing (SA) and particle swarm optimization (PSO) are discussed in detail. Multi-objective optimization has been dealt in a separate chapter, where the working principles of a few approaches are explained. 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 then explained, and the last chapter deals with the applications of soft computing in two different fields of research. It has been written to fulfill the requirements of a large number of readers belonging to various disciplines of engineering and general sciences. The algorithms are discussed with a number of solved numerical examples. It will be very much helpful to the students, scientists and practicing engineers.
942			_2ddc _cBK
999			_c2447 _d2447