Fuzzy, rough and intuitionistic fuzzy set approaches for data handling : theory and applications / Tanmoy Som, Oscar Castillo, Anoop Kumar Tiwari, Shivam Shreevastava, editors.

This book facilitates both the theoretical background and applications of fuzzy, intuitionistic fuzzy and rough, fuzzy rough sets in the area of data science. This book provides various individual, soft computing, optimization and hybridization techniques of fuzzy and intuitionistic fuzzy sets with...

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Bibliographic Details
Other Authors: Som, Tanmoy (Editor), Castillo, Oscar, 1959- (Editor), Tiwari, Anoop Kumar (Editor), Shreevastava, Shivam (Editor)
Format: eBook
Language:English
Published: Singapore : Springer, [2023]
Series:Forum for interdisciplinary mathematics.
Subjects:
Online Access:Click for online access
Description
Summary:This book facilitates both the theoretical background and applications of fuzzy, intuitionistic fuzzy and rough, fuzzy rough sets in the area of data science. This book provides various individual, soft computing, optimization and hybridization techniques of fuzzy and intuitionistic fuzzy sets with rough sets and their applications including data handling and that of type-2 fuzzy systems. Machine learning techniques are effectively implemented to solve a diversity of problems in pattern recognition, data mining and bioinformatics. To handle different nature of problems, including uncertainty, the book highlights the theory and recent developments on uncertainty, fuzzy systems, feature extraction, text categorization, multiscale modeling, soft computing, machine learning, deep learning, SMOTE, data handling, decision making, Diophantine fuzzy soft set, data envelopment analysis, centrally measures, social networks, VolterraFredholm integro-differential equation, Caputo fractional derivative, interval optimization, decision making, classification problems. This book is predominantly envisioned for researchers and students of data science, medical scientists and professional engineers.
Physical Description:1 online resource (xiii, 276 pages) : illustrations (chiefly color).
ISBN:9789811985669
9811985669
Source of Description, Etc. Note:Print version record.