Hybrid soft computing models applied to graph theory / Muhammad Akram, Fariha Zafar.
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 intuitio...
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| Main Authors: | , |
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| Format: | Ebook |
| Language: | English |
| Published: |
Cham, Switzerland :
Springer,
[2020]
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| Series: | Studies in fuzziness and soft computing ;
v. 380. |
| Subjects: | |
| Online Access: | Springer eBooks |
| Summary: | 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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| Physical Description: | 1 online resource (xxv, 434 pages) : illustrations (some colour). |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 303016019X 3030160203 9783030160197 9783030160203 |
| ISSN: | 1434-9922 ; |