Impact of artificial intelligence in the reduction of electrical consumption in wastewater treatment plants: a review
Francisco Esteves, J.C. Cardoso, Sérgio Leitão, E. J. Solteiro Pires
University of Trás-os-Montes and Alto Douro
内容与影响
Wastewater Treatment Plants are energy-intensive consumers. Thus, understanding their energy consumption to achieve efficient management can provide considerable environmental and economic benefits. The complexity of the treatment systems, the non-linearity, and the uncertainty and data availability limitations require the use of energy audits, according to a truly holistic view, as well as the use of alternative analysis models and decision support, more efficient than traditional modeling techniques.   The purpose of this review paper is to identify practical examples of the main lines of thought using Artificial Intelligence algorithms used to reduce the consumption of electrical energy in the wastewater sector over the last years. From the several reviewed papers, from different research platforms, it is concluded that, despite the success of AI in reducing energy consumption, in particular Artificial Neural Networks, there is room to improve energy efficiency consumption, identifying or quantifying inefficiency phenomena associated with data collection.
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
回答优先基于摘要、文献信息与可获取全文;依据不足时会明确说明。
学术脉络
学科主题
物理Water Quality Monitoring Technologies
Machine Learning and ELM · Internet of Things and AI
参考文献 71
此处列出前 3 条
施引文献 4
按被引量排序,此处列出前 3 条