Artificial Intelligence Systems Based on Hybrid Neural Networks

Theory and Applications
Author(s): Michael Zgurovsky, Victor Sineglazov, Elena Chumachenko
Format: Paperback
Publisher: Springer Nature Switzerland AG, Switzerland
Imprint: Springer Nature Switzerland AG
ISBN-13: 9783030484552, 978-3030484552

Synopsis

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 [url] 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 [url] 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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