Application of Artificial Neural Networks for Catalysis

2021/10/03 by Zhiqiang Liu, Liu, Zhiqiang, Wentao Zhou +1
Computer Science · Engineering · #Advanced Data Processing Techniques #FOS: Electrical engineering #Fuzzy Logic and Control Systems #I.2 #Neural Networks and Applications #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2110.00924

openalex publication_date 2021/10/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Catalyst, as an important material, plays a crucial role in the development of chemical industry. By improving the performance of the catalyst, the economic benefit can be greatly improved. Artificial neural network (ANN), as one of the most popular machine learning algorithms, relies on its good ability of nonlinear transformation, parallel processing, self-learning, self-adaptation and good associative memory, has been widely applied to various areas. Through the optimization of catalyst by ANN, the consumption of time and resources can be greatly reduced and greater economic benefits can be obtained. In this review, we show how this powerful technique helps people address the highly complicated problems and accelerate the progress of the catalysis community.

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