Сибирский федеральный университет

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: II International Scientific Conference on Advances in Material Science and Technology (CAMSTech-II 2021); Krasnoyarsk; Krasnoyarsk

Год издания: 2021

Идентификатор DOI: 10.1088/1757-899X/1181/1/012021

Аннотация: The problem is considered of designing a neural network system for control of road?materials compaction in real time. The system is designed to ensure the functioning of nondestructive technology in road construction. A model of an artificial neural network (ANN) for?monitoring the quality of compaction of road materials during the operation of vibrating rollers?in real time is obtained. The system provides normalization of the input data of the ANN model.?For the design of the ANN, the following methods were used: the least mean square deviation?method; Levenberg-Marquardt algorithm; backpropagation. The structure of a non-destructive?neural network system for monitoring compaction in real time is obtained. The results of?numerical simulation of a system with an ANN for predicting the compaction coefficient of road?materials are presented.?

Журнал: IOP Conference Series: Materials Science and Engineering

Выпуск журнала: 1181

Номера страниц: 012021-012021

Издатель: IOP Publishing Ltd

• Nabizhanov Zh.I. (Siberian Federal University)
• Prokopev A.P. (Siberian Federal University)
• Emelyanov R.T. (Siberian Federal University)

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