Skip to content
Research Article Open access CC BY 4.0

Research on Chemical Process Optimization Based on Artificial Neural Network Algorithm

Fei Liang, Taowen Zhang

Asian Journal of Research in Computer Science · pp. 12–24 · Published 3 Dec 2021

10.9734/ajrcos/2021/v12i430291

Abstract

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.

Artificial neural network chemical process process optimization

Cited by 4

Optimization Method for the PVB Resin Process Parameters Based on the Quality Index Prediction Model

Tongming Xu, Haiming Zhang, Bozhao Li · Journal of Chemical Engineering of Japan · 2025

Optimizing the process parameters in stirred-media mills using mathematical modeling

Keqi Guo, Hongji Chen, Qinshan Liu · Particulate Science and Technology · 2025

Article metrics

Real usage data collected on this platform.

0

Page views

0

PDF downloads

0

Outbound clicks

4

Citations

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

No views recorded yet.

Traffic sources

Referring site, by host.

No traffic recorded yet.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.