Hierarchical Modular Granular Neural Net
โ Daniela Sanchez, Patricia Melin
๐ Library
๐
2017
๐ Springer
๐ English
โฆ LIBER โฆ
๐
Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation
โ Scribed by Daniela Sanchez, Patricia Melin (auth.)
- Publisher
- Springer International Publishing
- Year
- 2016
- Tongue
- English
- Leaves
- 107
- Series
- SpringerBriefs in Applied Sciences and Technology
- Edition
- 1
- Category
- Library
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โฆ 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.
โฆ Table of Contents
Front Matter....Pages i-viii
Introduction....Pages 1-3
Background and Theory....Pages 5-11
Proposed Method....Pages 13-36
Application to Human Recognition....Pages 37-40
Experimental Results....Pages 41-80
Conclusions....Pages 81-81
Back Matter....Pages 83-101
โฆ Subjects
Computational Intelligence;Artificial Intelligence (incl. Robotics);Mathematical Models of Cognitive Processes and Neural Networks
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