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Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation (SpringerBriefs in Applied Sciences and Technology)

By: Daniela Sanchez (Author) , Patricia Melin (Author)

Extended Catalogue

Ksh 9,950.00

Format: Paperback or Softback

ISBN-10: 331928861X

ISBN-13: 9783319288611

Collection / Series: SpringerBriefs in Applied Sciences and Technology

Collection Type: Publisher collection

Edition statement: 1st ed. 2016

Publisher: Springer International Publishing AG

Imprint: Springer International Publishing AG

Country of Manufacture: CH

Country of Publication: GB

Publication Date: Mar 2nd, 2016

Publication Status: Active

Product extent: 101 Pages

Product Classification / Subject(s): Mathematical modelling
Artificial intelligence

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The techniquesused and combined in the proposed method are modular neural networks (MNNs)with a Granular Computing (GrC) approach, thus resulting in a new concept ofMNNs;

In this book, anew method for hybrid intelligent systems is proposed. The proposed method isbased on a granular computing approach applied in two levels. The techniquesused and combined in the proposed method are modular neural networks (MNNs)with a Granular Computing (GrC) approach, thus resulting in a new concept ofMNNs; modular granular neural networks (MGNNs). In addition fuzzy logic (FL)and hierarchical genetic algorithms (HGAs) are techniques used in this researchwork to improve results. These techniques are chosen because in other workshave demonstrated to be a good option, and in the case of MNNs and HGAs, thesetechniques allow to improve the results obtained than with their conventionalversions; respectively artificial neural networks and genetic algorithms.


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