Data-Mining for Processes in Chemistry, Materials, and Engineering

Processes

Hao Li¹  Zhe-Ze Zhao²  Zhien Zhang³ 

[1] College of Chemistry, Sichuan University, Chengdu 610064, China;School of Life Sciences and State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China;William G. Lowrie Department of Chemical and Biomolecular Engineering, The Ohio State University, 151 West Woodruff Avenue, Columbus, OH 43210, USA;

关键词: data-mining;    machine learning;    neural networks;    chemistry;    materials;    engineering;    energy;   

DOI  :  10.3390/pr7030151

来源: DOAJ

【 摘 要 】

With the rapid development of machine learning techniques, data-mining for processes in chemistry, materials, and engineering has been widely reported in recent years. In this discussion, we summarize some typical applications for process optimization, design, and evaluation of chemistry, materials, and engineering. Although the research and application targets are various, many important common points still exist in their data-mining. We then propose a generalized strategy based on the philosophy of data-mining, which should be applicable for the design and optimization targets for processes in various fields with both scientific and industrial purposes.

【 授权许可】

Unknown