Artificial Intelligence Systems Based on Hybrid Neural Networks: Theory and Applications

Artificial Intelligence Systems Based on Hybrid Neural Networks: Theory and Applications

Author
Michael Zgurovsky, Victor Sineglazov, Elena Chumachenko
Publisher
Springer International Publishing;Springer
Language
English
Edition
1st ed.
Year
2021
Page
XV, 512
ISBN
9783030484521,9783030484538
File Type
pdf
File Size
22.8 MiB

This book is intended for specialists as well as students and graduate students in the field of artificial intelligence, robotics and information technology. It is will also appeal to a wide range of readers interested in expanding the functionality of artificial intelligence systems. One of the pressing problems of modern artificial intelligence systems is the development of integrated hybrid systems based on deep learning. Unfortunately, there is currently no universal methodology for developing topologies of hybrid neural networks (HNN) using deep learning. The development of such systems calls for the expansion of the use of neural networks (NS) for solving recognition, classification and optimization problems. As such, it is necessary to create a unified methodology for constructing HNN with a selection of models of artificial neurons that make up HNN, gradually increasing the complexity of their structure using hybrid learning algorithms.

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