Artificial Intelligence Systems Based on Hybrid Neural Networks

Download or read book Artificial Intelligence Systems Based on Hybrid Neural Networks written by Michael Zgurovsky and published by Springer Nature. This book was released on 2020-09-03 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.