Fuzzy, Rough and Intuitionistic Fuzzy Set Approaches for Data Handling - Theory and Applications (Hardcover, 1st ed. 2023)

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, Volterra–Fredholm 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.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	Forum for Interdisciplinary Mathematics
Release date:	March 2023
First published:	2023
Editors:	Tanmoy Som • Oscar Castillo • Anoop Kumar Tiwari • Shivam Shreevastava
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	276
Edition:	1st ed. 2023
ISBN-13:	978-981-19-8565-2
Categories:	Books > Science & Mathematics > Biology, life sciences > Molecular biology Books > Medicine > Nursing & ancillary services > Biomedical engineering > General Books > Science & Mathematics > Mathematics > Applied mathematics > General Books > Computing & IT > Applications of computing > Databases > Data mining
LSN:	981-19-8565-0
Barcode:	9789811985652

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