Soft computing techniques are no longer limited to the arena of
computer science. The discipline has an exponentially growing
demand in other branches of science and engineering and even into
health and social science. This book contains theory and
applications of soft computing in engineering, health, and social
and applied sciences. Different soft computing techniques such as
artificial neural networks, fuzzy systems, evolutionary algorithms
and hybrid systems are discussed. It also contains important
chapters in machine learning and clustering. This book presents a
survey of the existing knowledge and also the current state of art
development through original new contributions from the
researchers. This book may be used as a one-stop reference book for
a broad range of readers worldwide interested in soft computing. In
each chapter, the preliminaries have been presented first and then
the advanced discussion takes place. Learners and researchers from
a wide variety of backgrounds will find several useful tools and
techniques to develop their soft computing skills. This book is
meant for graduate students, faculty and researchers willing to
expand their knowledge in any branch of soft computing. The readers
of this book will require minimum prerequisites of undergraduate
studies in computation and mathematics.
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