{"title":"Application and innovation of artificial intelligence models in wastewater treatment","authors":"Wen-Long Xu, Ya-Jun Wang, Yi-Tong Wang, Jun-Guo Li, Ya-Nan Zeng, Hua-Wei Guo, Huan Liu, Kai-Li Dong, Liang-Yi Zhang","doi":"10.1016/j.jconhyd.2024.104426","DOIUrl":null,"url":null,"abstract":"<div><p>At present, as the problem of water shortage and pollution is growing serious, it is particularly important to understand the recycling and treatment of wastewater. Artificial intelligence (AI) technology is characterized by reliable mapping of nonlinear behaviors between input and output of experimental data, and thus single/integrated AI model algorithms for predicting different pollutants or water quality parameters have become a popular method for simulating the process of wastewater treatment. Many AI models have successfully predicted the removal effects of pollutants in different wastewater treatment processes. Therefore, this paper reviews the applications of artificial intelligence technologies such as artificial neural networks (ANN), adaptive network-based fuzzy inference system (ANFIS) and support vector machine (SVM). Meanwhile, this review mainly introduces the effectiveness and limitations of artificial intelligence technology in predicting different pollutants (dyes, heavy metal ions, antibiotics, etc.) and different water quality parameters such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), total nitrogen (TN) and total phosphorus (TP) in wastewater treatment process, involving single AI model and integrated AI model. Finally, the problems that need further research together with challenges ahead in the application of artificial intelligence models in the field of environment are discussed and presented.</p></div>","PeriodicalId":15530,"journal":{"name":"Journal of contaminant hydrology","volume":"267 ","pages":"Article 104426"},"PeriodicalIF":3.5000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of contaminant hydrology","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S016977222400130X","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
At present, as the problem of water shortage and pollution is growing serious, it is particularly important to understand the recycling and treatment of wastewater. Artificial intelligence (AI) technology is characterized by reliable mapping of nonlinear behaviors between input and output of experimental data, and thus single/integrated AI model algorithms for predicting different pollutants or water quality parameters have become a popular method for simulating the process of wastewater treatment. Many AI models have successfully predicted the removal effects of pollutants in different wastewater treatment processes. Therefore, this paper reviews the applications of artificial intelligence technologies such as artificial neural networks (ANN), adaptive network-based fuzzy inference system (ANFIS) and support vector machine (SVM). Meanwhile, this review mainly introduces the effectiveness and limitations of artificial intelligence technology in predicting different pollutants (dyes, heavy metal ions, antibiotics, etc.) and different water quality parameters such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), total nitrogen (TN) and total phosphorus (TP) in wastewater treatment process, involving single AI model and integrated AI model. Finally, the problems that need further research together with challenges ahead in the application of artificial intelligence models in the field of environment are discussed and presented.
期刊介绍：
The Journal of Contaminant Hydrology is an international journal publishing scientific articles pertaining to the contamination of subsurface water resources. Emphasis is placed on investigations of the physical, chemical, and biological processes influencing the behavior and fate of organic and inorganic contaminants in the unsaturated (vadose) and saturated (groundwater) zones, as well as at groundwater-surface water interfaces. The ecological impacts of contaminants transported both from and to aquifers are of interest. Articles on contamination of surface water only, without a link to groundwater, are out of the scope. Broad latitude is allowed in identifying contaminants of interest, and include legacy and emerging pollutants, nutrients, nanoparticles, pathogenic microorganisms (e.g., bacteria, viruses, protozoa), microplastics, and various constituents associated with energy production (e.g., methane, carbon dioxide, hydrogen sulfide).
The journal''s scope embraces a wide range of topics including: experimental investigations of contaminant sorption, diffusion, transformation, volatilization and transport in the surface and subsurface; characterization of soil and aquifer properties only as they influence contaminant behavior; development and testing of mathematical models of contaminant behaviour; innovative techniques for restoration of contaminated sites; development of new tools or techniques for monitoring the extent of soil and groundwater contamination; transformation of contaminants in the hyporheic zone; effects of contaminants traversing the hyporheic zone on surface water and groundwater ecosystems; subsurface carbon sequestration and/or turnover; and migration of fluids associated with energy production into groundwater.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
