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Industrial Automatic Control Systems and Controllers

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Continuous Acquisition Support for Adaptive Machine Learning of Artificial Neural Networks with Feedback
A.V. Ostroukh, N.O. Listov

The article review of the teaching methods of artificial neural networks and methods for accelerating learning. The structure of the Continuous Acquisition Supp for adaptive machine learning of artificial neural networks with feedback to improve the efficiency of pattern recognition in deep learning neural networks is proposed. Solutions allow training neural networks with greater efficiency, reaching the required level of accuracy in less time. The use of such acceleration does not require knowledge of the mathematical apparatus from the developer and does not require interruption of the learning process. The proposed approach ensures the continuity of the learning process of an artificial neural network. Distributed work of the system allows not only to transact data from different points, but also to process them on different machines more effi ciently.
Keywords: Deep Learning Neural Networks (DLNN); Machine Learning (ML); Continuous Acquisition Support (CAS); Integrated Information Space (IIS).

Contacts: E-mail: ostroukh@mail.ru, E-mail: necron9631@yandex.ru

Pp. 10-19.

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