Hybrid Soft Computing Models Applied to Graph Theory is popular PDF and ePub book, written by Muhammad Akram in 2019-04-05, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Hybrid Soft Computing Models Applied to Graph Theory can be Read Online from any device for your convenience.
Hybrid Soft Computing Models Applied to Graph Theory Book PDF 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.
Detail Book of Hybrid Soft Computing Models Applied to Graph Theory PDF
- Author : Muhammad Akram
- Release : 05 April 2019
- Publisher : Springer
- ISBN : 9783030160203
- Genre : Technology & Engineering
- Total Page : 434 pages
- Language : English
- PDF File Size : 21,9 Mb
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