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Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation

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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.

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Series Title

-

Call Number

004 SAN h

Publisher

: ., 2015

Collation

VIII, 101

Language

English

ISBN/ISSN

978-3-319-28861-1

Classification

004

Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

-

Subject(s)

Computational Intelligence,

Specific Detail Info

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Statement of Responsibility

Daniela Sanchez , Patricia Melin

Other Information

Cataloger

Khusnun

Source

-

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Journal Volume

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Journal Issue

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Subtitle

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