This book is the result of our motivation to provide a student-friendly text book on soft computing. With the growing importance of computational intelligence in diverse application areas, soft computing is fast gaining importance and popularity in the academic world. Soft computing is a branch of artificial intelligence that provides approximate solutions to difficult problems for which traditional methods do not fit in as solution providers. Classical methods find it difficult or impossible to solve it. Currently, this subject is included either as elective or core, in various undergraduate and post graduate curricula in computer science and engineering, information technology, master of computer applications, and other related courses. This book covers the syllabi of the soft computing papers in curricula of Anna University. We hope that this book will serve the requirements of the students and researchers interested in this field.
The purpose of this book is to introduce the reader
- To introduce the ideas of fuzzy sets, fuzzy logic and use of heuristics based on human experience.
- To provide the mathematical background for carrying out the optimization associated with neural network learning
- To learn various evolutionary Algorithms.
- To become familiar with neural networks that can learn from available examples and generalize to form appropriate rules for inference systems.
- To introduce case studies utilizing the above and illustrate the Intelligent behavior of programs based on soft computing
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