Artificial intelligence (AI) is a powerful tool that is commonly applied in engineering multi-
disciplines owing to its functionality to resolve real-world problems where deterministic …

Numerous conventional methods are available for analyzing various water quality
parameters to determine the water quality index. However, ongoing surveillance is …

This research focuses on applying artificial neural networks with nonlinear transformation
(ANNs) models to predict the performance of wastewater treatment plant (WWTP) processes …

Abstract Machine learning (ML) is a data-driven approach that can be applied to design,
analyze, predict, and optimize a process based on existing data. Recently, ML has found its …

The aim of this paper is to describe the state-of-the art computer-based techniques for data
analysis to improve operation of wastewater treatment plants. A comprehensive review of …

Water pollution generated from intensive anthropogenic activities has emerged as a critical
issue concerning ecosystem balance and livelihoods worldwide. Although optimizing …

Water resources of desired quality and quantity are the foundation for human survival and
sustainable development. To better protect the water environment and conserve water …

This article explores the transformative potential of integrating artificial intelligence (AI) with
environmental science to address pressing challenges and foster sustainable solutions. The …

Improving wastewater treatment processes is becoming increasingly important, due to more
stringent effluent quality requirements, the need to reduce energy consumption and …

Modelling wastewater processes supports tasks such as process prediction, soft sensing,
data analysis and computer assisted design of wastewater systems. Wastewater treatment …