Comparative analysis of the use of a neural network in the problem of identification properties of materials
Abstract
Comparative analysis of the use of a neural network in the problem of identification properties of materials
Incoming article date: 21.10.2021The article is devoted to the use of artificial intelligence tools to solve technical problems in the construction industry. It is noted that the use of neural networks will allow taking into account the behavior of materials in various experimental conditions. The authors present a comparative analysis of approaches to neural network training, in particular, the structures of multilayer and LSTM networks are considered. It is established that LSTM networks are more effective in solving problems of identification properties of materials.
Keywords: neural network, non-destructive testing, identification task, multilayer network, LSTM network, impact indentation, indentation, strength properties of materials, neural network technologies, statistical distribution