Offered to: UG & PG
Introduction to soft computing, hard computing, Need for soft computing; Neurons and neural networks; Basic models of artificial neural networks – single-layer perceptron, multilayer perceptron; Radial basis function networks; SOM; Recurrent neural networks; Training of neural network; Applications of neural networks in mechanical engineering; Introduction to fuzzy sets, Fuzzy reasoning and clustering; Optimization tools – traditional and non-traditional, genetic algorithms, simulated annealing etc.; Combined techniques – Genetic Algorithms–Fuzzy Logic, Genetic Algorithms–Neural Networks, Neural Networks– Fuzzy Logic.
 D. K. Pratihar, Soft Computing, Narosa Publishing House, 2008.
 S. Haykin, Neural Networks: A Comprehensive Foundation, 2nd Ed, Pearson Education, 1999.
 G. Chen and T. T. Pham, Introduction to Fuzzy Sets, Fuzzy Logic, and Fuzzy Control Systems, CRC Press, 2001.
 P. M. Dixit, U. S. Dixit, Modeling of metal forming and machining processes: by finite element and soft computing methods, 1st Ed, Springer-Verlag, 2008.
 K. Deb, Optimization for Engineering Design: Algorithms and Examples, Prentice Hall, 2006.
 R. A. Aliev, R. R. Aliev, Soft Computing and its Applications, World Scientific Publishing Co. Pte. Ltd., 2001.