Overview
- Provides a unified framework describing how fuzzy rough granular neural network technologies can be judiciously formulated and used in building efficient pattern recognition models
- Is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and applications
- Highlights applications in bioinformatics
- Includes supplementary material: sn.pub/extras
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 712)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (7 chapters)
-
Front Matter
-
Back Matter
Keywords
About this book
This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses the formation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting in efficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules,.
The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application. It covers the latest findings as well as directions forfuture research, particularly highlighting bioinformatics applications. The book is recommended for both students and practitioners working in computer science, electrical engineering, data science, system design, pattern recognition, image analysis, neural computing, social network analysis, big data analytics, computational biology and soft computing.
Authors and Affiliations
Bibliographic Information
Book Title: Granular Neural Networks, Pattern Recognition and Bioinformatics
Authors: Sankar K. Pal, Shubhra S. Ray, Avatharam Ganivada
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-319-57115-7
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-57113-3Published: 10 May 2017
Softcover ISBN: 978-3-319-86079-4Published: 25 July 2018
eBook ISBN: 978-3-319-57115-7Published: 02 May 2017
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XIX, 227
Number of Illustrations: 23 b/w illustrations, 31 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Computational Biology/Bioinformatics