Hybrid Soft Computing Models Applied to Graph Theory

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Hybrid Soft Computing Models Applied to Graph Theory

Management decision making Operational research Data mining Artificial intelligence Expert systems / knowledge-based systems

Authors: Muhammad Akram, Fariha Zafar

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Collection: Studies in Fuzziness and Soft Computing

Language: English

Published by: Springer

Published on: 5th April 2019

Format: LCP-protected ePub

Size: 52 Mb

ISBN: 9783030160203


Book Description

This book describes a set of hybrid fuzzy models showing how to use them to deal with incomplete and/or vague information in different kind of decision-making problems. Based on the authors’ research, it offers a concise introduction to important models, ranging from rough fuzzy digraphs and intuitionistic fuzzy rough models to bipolar fuzzy soft graphs and neutrosophic graphs, explaining how to construct them. For each method, applications to different multi-attribute, multi-criteria decision-making problems, are presented and discussed. The book, which addresses computer scientists, mathematicians, and social scientists, is intended as concise yet complete guide to basic tools for constructing hybrid intelligent models for dealing with some interesting real-world problems. It is also expected to stimulate readers’ creativity thus offering a source of inspiration for future research.

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