Uncertainty Management with Fuzzy and Rough Sets: Recent Advances and Applications

Uncertainty Management with Fuzzy and Rough Sets: Recent Advances and Applications

ISBN-10:
3030104621
ISBN-13:
9783030104627
Pub. Date:
01/23/2019
Publisher:
Springer International Publishing
ISBN-10:
3030104621
ISBN-13:
9783030104627
Pub. Date:
01/23/2019
Publisher:
Springer International Publishing
Uncertainty Management with Fuzzy and Rough Sets: Recent Advances and Applications

Uncertainty Management with Fuzzy and Rough Sets: Recent Advances and Applications

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Overview

This book offers a timely overview of fuzzy and rough set theories and methods. Based on selected contributions presented at the International Symposium on Fuzzy and Rough Sets, ISFUROS 2017, held in Varadero, Cuba, on October 24-26, 2017, the book also covers related approaches, such as hybrid rough-fuzzy sets and hybrid fuzzy-rough sets and granular computing, as well as a number of applications, from big data analytics, to business intelligence, security, robotics, logistics, wireless sensor networks and many more. It is intended as a source of inspiration for PhD students and researchers in the field, fostering not only new ideas but also collaboration between young researchers and institutions and established ones.


Product Details

ISBN-13: 9783030104627
Publisher: Springer International Publishing
Publication date: 01/23/2019
Series: Studies in Fuzziness and Soft Computing , #377
Edition description: 1st ed. 2019
Pages: 413
Product dimensions: 6.10(w) x 9.25(h) x (d)

Table of Contents

A proposal of hybrid fuzzy clustering algorithm with application in fault diagnosis.- Solving a Fuzzy Tourist Trip Design Problem with Clustered Points of Interest.- Fully Fuzzy Linear Programming Model For the Berth Allocation Problem with Two Quays.- Ideal reference method with linguistic labels: a comparison with LTOPSIS.- Fuzzy cognitive maps for evaluating software usability.- Ideal reference method with linguistic labels: a comparison with LTOPSIS.- A proposal of hybrid fuzzy clustering algorithm with application in fault diagnosis.

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