Concepts of Soft Computing : Fuzzy and ANN with Programming

Snehashish Chakraverty

ISBN 10: 9811374295 / ISBN 13: 9789811374296

Editore: Springer Nature Singapore, Springer Nature Singapore, 2019

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Druck auf Anfrage Neuware - Printed after ordering - 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.

Codice articolo 9789811374296

Dati bibliografici

• Titolo: Concepts of Soft Computing : Fuzzy and ANN with Programming
• Editore: Springer Nature Singapore, Springer Nature Singapore
• Data di pubblicazione: 2019
• Lingua: Inglese
• ISBN 10: 9811374295
• ISBN 13: 9789811374296
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 241 L x 160 A x 17 P (millimetri) 241 millimetri di larghezza per 160 millimetri di altezza per 17 millimetri di profondità
• Peso: 540 grammi

Descrizione articolo

Riassunto

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

Informazioni sull?autore

Prof. Snehashish Chakraverty has 27 years of experience as a researcher and is currently a Professor at the Department of Mathematics at National Institute of Technology, Rourkela, Odisha. He holds an M.Sc. in Mathematics, M.Phil. in Computer Applications and a Ph.D. from IIT Roorkee. He then pursued postdoctoral research at the Institute of Sound and Vibration Research (ISVR), University of Southampton, U.K. and at the Faculty of Engineering and Computer Science, Concordia University, Canada. He has authored about 14 books and published more than 314 research papers in respected journals and conferences.

Prof. Chakraverty is on the editorial boards of various international journals, book series and conferences and is also the chief editor of the International Journal of Fuzzy Computation and Modelling (IJFCM), Inderscience Publisher, Switzerland and is a guest editor for various other journals. He is recipient of few prestigious awards viz. Indian National Science Acdemy (INSA) nomination under International Collaboration/Bilateral Exchange Program (with Czech Republic), Platinum Jubilee ISCA Lecture Award (2014), CSIR Young Scientist (1997), BOYSCAST (DST), UCOST Young Scientist (2007, 2008), Golden Jubilee Director’s (CBRI) Award (2001), Roorkee University Gold Medals (1987, 1988) for first positions in M. Sc. and M. Phil. etc. His current research areas include soft computing and machine intelligence, artificial neural networks, fuzzy and interval computations, numerical analysis, differential equations, mathematical modelling, uncertainty modelling, vibration and inverse vibration problems.

Dr. Deepti Moyi Sahoo is currently Assistant Professsor at O.P. Jindal University, Punjipathra, Raigarh, Chhattisgarh in the Department of Mathematics. She completed her Master of Science degree in Mathematics at National Institute of Technology, in 2010. She received her Ph.D. from the same institute in 2017.

Dr. Sahoo has co-authored good number of research papers and a book chapter. Her current research areas include interval analysis, fuzzy set theory, artificial neural networks, interval and fuzzy neural networks, functional link neural networks and structural system identification problems.

Nisha Rani Mahato is currently pursuing her Ph.D. at the Department of Mathematics at the National Institute of Technology, Rourkela, Odisha. She completed her Master of Science degree in Mathematics at the National Institute of Technology, in 2011. She was awarded Raman Charpak Fellowship-2016 (RCF-2016) by CEFIPRA, New Delhi. Also, she had been awarded best paper at the 38th Annual Conference of Orissa Mathematical Society in 2011 and best poster in mathematics at Research Scholar Week 2018, NIT Rourkela.

She has participated in various conferences/workshops and published good number of research papers, a book chapter and a book. Her current research areas include interval analysis, fuzzy set theory, interval/fuzzy eigenvalue problems, interval/fuzzy simultaneous equations and interval/fuzzy differential equations.