Artificial Neural Network (ANN) is established by imitating the human brain's nerve thinking mode. Because of its strong nonlinear mapping ability, fault tolerance and self-learning ability, it is widely used in many fields such as intelligent driving, signal processing, process control and so on. This article introduces the basic principles, development history and three common neural network types of artificial neural networks, BP neural network, RBF neural network and convolutional neural network, focusing on the research progress of the practical application of neural networks in chemical process optimization.
As an important part of artificial intelligence and machine learning, artificial neural network (ANN) has been widely used because of its strong information processing and autonomous learning capabilities. In this paper, the development history of ANN is summarized, and the three common types of ANN are introduced: MLP neural network, BP neural network and recurrent neural network. Finally the practical application of ANN in chemical production forecasting are analyzed and an outlook on its development direction is prospected.
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