Application of artificial intelligence techniques in textile wastewater decolorisation fields: A systematic and citation network analysis review

被引：11

作者：

Liu, Senbiao ^{[1
]}

Lo, Chris K. Y. ^{[1
]}

Kan, Chi-wai ^{[1
]}

机构：

[1] Hong Kong Polytech Univ, Inst Text & Clothing, Kowloon, Hong Kong, Peoples R China

来源：

COLORATION TECHNOLOGY | 2022年 / 138卷 / 02期

关键词：

RESPONSE-SURFACE METHODOLOGY; ALGORITHM-BASED OPTIMIZATION; PHOTOELECTRO-FENTON PROCESS; METHYLENE-BLUE DYE; NEURAL-NETWORK; GENETIC ALGORITHM; AQUEOUS-SOLUTION; AZO-DYE; PHOTOCATALYTIC DEGRADATION; OPERATIONAL PARAMETERS;

D O I：

10.1111/cote.12589

中图分类号：

O69 [应用化学];

学科分类号：

081704 ;

摘要：

This study reviewed 155 journal articles to examine how artificial intelligence techniques are being applied in textile coloration and related fields. Distribution of the reviewed articles was assessed in terms of the type of journals, year of publication, methods, and research background. Based on the citation network analysis method, an objective approach, CitNetExplorer and VOSviewer are used to identify the clusters. It is found that artificial intelligence techniques are mainly three-layer artificial neural networks with different designs, which are mainly used in textile wastewater decolorisation fields, including wastewater treatment and colour fading, such as colour prediction and real-time monitoring of textile wastewater, dye removal efficiency, and dye degradation. Finally, the future research direction and limitations of this article are put forward.

引用

页码：117 / 136

页数：20

共 178 条

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