Artificial intelligence systems based on hybrid neural networks [electronic resource] : theory and applications / Michael Zgurovsky, Victor Sineglazov, Elena Chumachenko.

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Artificial intelligence systems based on hybrid neural networks [electronic resource] : theory and applications / Michael Zgurovsky, Victor Sineglazov, Elena Chumachenko.

9783030484538 (electronic bk.)
303048453X (electronic bk.)
3030484521
9783030484521

Cham : Springer, [2021]

English

1 online resource.

10.1007/978-3-030-48453-8 doi
10.1007/978-3-030-48

Q335

006.3

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.

Includes bibliographical references and index.

Access limited to authorized users.

Studies in computational intelligence ; v. 904.

Print version: 9783030484521

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