Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation
| By: | Daniela Sanchez; Patricia Melin |
| Publisher: | Springer Nature |
| Print ISBN: | 9783319288611 |
| eText ISBN: | 9783319288628 |
| Edition: | 0 |
| Copyright: | 2016 |
| Format: | Page Fidelity |
eBook Features
Instant Access
Purchase and read your book immediately
Read Offline
Access your eTextbook anytime and anywhere
Study Tools
Built-in study tools like highlights and more
Read Aloud
Listen and follow along as Bookshelf reads to you
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.