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Handbook of Research on Fuzzy and Rough Set Theory in Organizational Decision Making
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Author(s)/Editor(s): Arun Kumar Sangaiah (VIT University, India), Xiao-Zhi Gao (University of Eastern Finland, Finland)and Ajith Abraham (Machine Intelligence Research Labs, USA)
Copyright: ©2017
DOI: 10.4018/978-1-5225-1008-6
ISBN13: 9781522510086
ISBN10: 1522510087
EISBN13: 9781522510093
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DescriptionSoft computing techniques are innovative tools that use nature-inspired algorithms to run predictive analysis of industries from business to software measurement. These tools have gained momentum in recent years for their practicality and flexibility. The Handbook of Research on Fuzzy and Rough Set Theory in Organizational Decision Making collects both empirical and applied research in the field of fuzzy set theory, and bridges the gap between the application of soft computational approaches and the organizational decision making process. This publication is a pivotal reference for business professionals, IT specialists, software engineers, and advanced students of business and information technology.
Reviews and Testimonials
Highly recommended for faculty, business people and students in Management and Computer Science. They would really appreciate the value of the book. It would also prove useful in electronics, both civil or mechanical where data needs to be analyzed to draw inference. This book would be of immense value to both managers who implement organizational programs and decision makers.
– Dr. K.DHINAKARAN, Rajalakshmi Institute of Technology, India
Computer scientists, electronic engineers, information scientists, and business scholars summarize constituent paradigms underlying fuzzy and rough sets and evolutionary computational intelligence methods, and show how to apply them in business decision making. Their topics include solving a basic inventory model in fuzzy and interval environments: a fuzzy and interval differential equation approach, a fuzzy dynamic programming problem for single additive constraint with additively separable return by means of trapezoidal membership functions, the genetic-based estimation of biomass using a geographical information system: study area Vellore, parameter reduction in soft set models and applications in decision making, and investment climate factors with reference to firm performance in Bangladesh: a prospective cohort study.
– Protoview Reviews
Author's/Editor's Biography
Arun Sangaiah (Ed.)
Arun Kumar Sangaiah has received his Master of Engineering (ME) degree in Computer Science and Engineering from the Government College of Engineering, Tirunelveli, Anna University, India. He had received his Doctor of Philosophy (PhD) degree in Computer Science and Engineering from the VIT University, Vellore, India. He is presently working as an Associate Professor in School of Computer Science and Engineering, VIT University, India. His area of interest includes software engineering, computational intelligence, wireless networks, bio-informatics, and embedded systems. He has authored more than 100 publications in different journals and conference of national and international repute. His current research work includes global software development, wireless ad hoc and sensor networks, machine learning, cognitive networks and advances in mobile computing and communications. He is an active member in Compute Society of India. Moreover, he has carried out number of funded research projects for Indian government agencies. Also, he was registered a one Indian patent in the area of Computational Intelligence. Besides, Prof. Arun Kumar Sangaiah is responsible for Editorial Board Member/Associate Editor of various international journals like International Journal of Intelligent Information Technologies (IGI), International Journal of Cloud Applications and Computing (IGI), International Journal of High Performance System (Inderscience), International Journal of Image Mining (Inderscience), International Journal of Intelligent Engineering and Systems, International Journal of Computational Systems Engineering (Inderscience) and Institute of Integrative Omics and Applied Biotechnology (IIOAB), etc. In addition, he has edited number of guest editorial special issues for various journals like Applied Soft Computing, Computers and Electrical Engineering (SCI) Future Generation Computer Systems (SCI), Neural Network World (SCI), Intelligent Automation & Soft Computing (SCI), Scientific World Journal (SCI) etc. Also, he has organized a number of special issues for Elsevier, Inderscience, Springer, Hindawi, and IGI publishers etc. Also he has acted as a book volume editor of various publishers for Taylor and Francis, Springer, IGI, etc. Furthermore, Prof. Sangaiah made outstanding efforts and contributions on the technical programme committee member of various reputed international/national conferences.
Xiao-Zhi Gao (Ed.)
Xiao-Zhi Gao received his B.Sc. and M.Sc. degrees from the Harbin Institute of Technology, China in 1993 and 1996, respectively. He obtained his D.Sc. (Tech.) degree from the Helsinki University of Technology (now Aalto University), Finland in 1999. He has been working as a professor at the University of Eastern Finland, Finland since 2018. Prof. Gao has published more than 400 technical papers in refereed journals and international conferences. His current Google Scholar H-index is 31. His research interests are nature-inspired computing methods with their applications in optimization, data mining, machine learning, control, signal processing, and industrial electronics.
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