人工智能模型在废水处理中的应用和创新
Wen-Long Xu1, Ya-Jun Wang1, Yi-Tong Wang1
1College of Metallurgy and Energy, North China University of Science and Technology, 21 Bohai Street, Tangshan 063210, China.
Journal of contaminant hydrology
|September 13, 2024
概括
人工智能 (AI) 模型有效地预测污染物和水质参数的废水处理结果. 这篇评论考察了AI.
科学领域:
- 环境科学 环境科学
- 水处理技术水处理技术
- 人工智能应用程序 人工智能应用程序
背景情况:
- 全球日益严重的水资源短缺和污染需要先进的废水回收和处理策略.
- 人工智能 (AI) 为模拟实验数据中的复杂非线性关系提供了强大的方法.
- 人工智能模型越来越受欢迎,用于模拟和预测废水处理过程和结果.
研究的目的:
- 审查人工智能技术在废水处理中的应用和有效性.
- 分析AI模型对各种污染物和水质参数的预测能力.
- 讨论AI在环境应用中的局限性和未来研究方向.
主要方法:
- 审查人工智能技术,包括人工神经网络 (ANN),基于自适应网络的模糊推理系统 (ANFIS) 和支持矢量机器 (SVM).
- 对单一和集成的人工智能模型进行分析,以预测污染物清除和水质参数.
- 对各种废水污染物 (染料,重金属,抗生素) 和参数 (BOD,COD,TN,TP) 的AI模型性能进行检查.
主要成果:
- 人工智能模型在预测废水处理中的污染物清除效率方面取得了显著的成功.
- 有效性取决于特定的AI模型,污染物类型和水质参数.
- 单一和集成的人工智能模型都在模拟复杂的治疗过程中表现出有希望的结果.
结论:
- 人工智能技术,特别是ANN,ANFIS和SVM,是预测废水处理性能的有价值工具.
- 需要进一步的研究来解决应用人工智能模型用于环境解决方案的局限性和挑战.
- 持续开发人工智能模型将增强废水管理和水资源可持续性.
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