245 10 |a Concepts of soft computing : |b fuzzy and ANN with programming / |c Snehashish Chakraverty, Deepti Moyi Sahoo, Nisha Rani Mahato.

505 0_ |a Fuzzy set theory: Soft computing -- Intervals -- Fuzzy sets -- Fuzzy numbers -- Fuzzy relations -- Fuzzy functions -- Fuzzy differentiation and integration -- Defuzzification -- Interval system of linear equations -- Interval eigenvalue problems. -- Artificial neural network: Artificial neural network terminologies -- McCulloch-Pitts neural network model -- Hebbian learning rule -- Perceptron learning rule -- Delta learning rule and backpropagation rule for multilayer perceptron.

520 __ |a This book discusses soft computing, which provides an efficient platform to deal with imprecision, uncertainty, vagueness and approximation in order to attain robustness and reliable computing. It explores two major concepts of soft computing: fuzzy set theory and neural networks, which relate to uncertainty handling and machine learning techniques respectively. Generally, fuzzy sets are considered as vague or uncertain sets having membership function lying between 0 and 1, and ANN is a type of artificial intelligence that attempts to imitate the way a human brain works by configuring specific applications, for instance pattern recognition or data classification, through learning processes. The book also presents C/MATLAB programming codes related to the basics of fuzzy set, interval arithmetic and ANN in a concise, practical and adaptable manner along, with simple examples and self-validation unsolved practice questions in few cases. -- |c Provided by publisher.