Hierarchical modular granular neural networks with fuzzy aggregation [electronic resource] / Daniela Sanchez, Patricia Melin.
Sanchez, Daniela, author.; Melin, Patricia, 1962- author.
2016
QA76.9.S63
Available Online

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Title Hierarchical modular granular neural networks with fuzzy aggregation [electronic resource] / Daniela Sanchez, Patricia Melin.
Author Sanchez, Daniela, author.
ISBN 9783319288628 (electronic book)
3319288628 (electronic book)
9783319288611
DOI https://doi.org/10.1007/978-3-319-28862-8
Published Switzerland : Springer, 2016.
Language English
Description 1 online resource (viii, 101 pages) : illustrations.
Item Number 10.1007/978-3-319-28862-8 doi
Call Number QA76.9.S63
Dewey Decimal Classification 006.3
Summary In this book, a new method for hybrid intelligent systems is proposed. The proposed method is based on a granular computing approach applied in two levels. The techniques used and combined in the proposed method are modular neural networks (MNNs) with a Granular Computing (GrC) approach, thus resulting in a new concept of MNNs; modular granular neural networks (MGNNs). In addition fuzzy logic (FL) and hierarchical genetic algorithms (HGAs) are techniques used in this research work to improve results. These techniques are chosen because in other works have demonstrated to be a good option, and in the case of MNNs and HGAs, these techniques allow to improve the results obtained than with their conventional versions; respectively artificial neural networks and genetic algorithms.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed March 1, 2016).
Added Author Melin, Patricia, 1962- author.
Series SpringerBriefs in applied sciences and technology. Computational intelligence.
Available in Other Form Print version: 9783319288611
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Introduction
Background and Theory
Proposed Method
Application to Human Recognition
Experimental Results
Conclusions.

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