文献类型：期刊文献

英文题名：Artificial neural network and its application research progress in chemical process

作者：Sun, Li[1]; Liang, Fei[1]; Cui, Wutai[1]

机构：[1] School of Chemical Engineering, East China University of Science and Technology, Shanghai, 200237, China

年份：2021

外文期刊名：arXiv

收录：EI(收录号：20210378508)

语种：英文

外文关键词：Biology - Catalysis - Complex networks - Distillation - Optimization - Process control

摘要：Most chemical processes, such as distillation, absorption, extraction, and catalytic reactions, are extremely complex processes that are affected by multiple factors. The relationships between their input variables and output variables are non-linear, and it is difficult to optimize or control them using traditional methods. Artificial neural network (ANN) is a systematic structure composed of multiple neuron models. Its main function is to simulate multiple basic functions of the nervous system of living organisms. ANN can achieve nonlinear control without relying on mathematical models, and is especially suitable for more complex control objects. This article will introduce the basic principles and development history of artificial neural networks, and review its application research progress in chemical process control, fault diagnosis, and process optimization. ? 2021, CC BY.