Description: Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Author(s): Daniela Sanchez, Patricia Melin Format: Paperback Publisher: Springer International Publishing AG, Switzerland Imprint: Springer International Publishing AG ISBN-13: 9783319288611, 978-3319288611 Synopsis 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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Book Title: Hierarchical Modular Granular Neural Networks with Fuzzy Aggre...
Item Height: 235 mm
Item Width: 155 mm
Series: Springerbriefs in Applied Sciences and Technology
Author: Daniela Sanchez, Patricia Melin
Publication Name: Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation
Format: Paperback
Language: English
Publisher: Springer International Publishing A&G
Subject: Computer Science, Mathematics
Publication Year: 2016
Type: Textbook
Item Weight: 1825 g
Number of Pages: 101 Pages
