Performance, because of this, Back Propagation Neural Network model trained with particle swarm. Output units depends on the activity of the hidden units and the weights between the hidden units and output units (Sivanandam and Deepa, 2006). Using hybrid ANN_BP model with principal transfer.
In this book the basic concepts of soft computing are dealt in detail with the relevant information and knowledge available for understanding the computing process. The various neural network concepts are explained with examples, highlighting the difference between various architectures. Fuzzy logic techniques have been clearly dealt with suitable examples. Genetic algorithm operators and the various classifications have been discussed in lucid manner, so that a beginner can understand the concepts with minimal effort. The book can be used as a handbook as well as a guide for students of all engineering disciplines, soft computing research scholars, management sector, operational research area, computer applications and for various professionals who work in this area.
Contents:- Chapter 1. Artificial Neural Network: An Introduction? Driver Hp Scanjet G3010 Xpadder. Supervised Learning Network? Associative Memory Networks? Unsupervised Learning Networks?
Special Networks? Introduction to Fuzzy Logic, Classical Sets and Fuzzy Sets? Classical Relations and Fuzzy Relations? Membership Functions? Fuzzy Arithmetic and Fuzzy Measures? Fuzzy Rule Base and Approximate Reasoning?
Fuzzy Decision Making? Fuzzy Logic Control Systems? Genetic Algorithm? Hybrid Soft Computing Techniques? Descargar Videos Gratis De Alejandra Guzman Yo Te Esperaba here. Applications of Soft Computing?
Soft Computing Techniques Using C and C++? MATLAB Environment for Soft Computing Techniques Bibliography Sample Question Paper 1 Sample Question Paper 2 Sample Question Paper 3 Sample Question Paper 4 Sample Question Paper 5 Index Printed Pages: 748. Bookseller Inventory # 12928.