A Comprehensive Review of Machine Learning for Water Quality Prediction over the Past Five Years

Journal of Marine Science and Engineering, Год журнала: 2024, Номер 12(1), С. 159 - 159

Опубликована: Янв. 13, 2024

Water quality prediction, a well-established field with broad implications across various sectors, is thoroughly examined in this comprehensive review. Through an exhaustive analysis of over 170 studies conducted the last five years, we focus on application machine learning for predicting water quality. The review begins by presenting latest methodologies acquiring data. Categorizing learning-based predictions into two primary segments—indicator prediction and index prediction—further distinguishes between single-indicator multi-indicator predictions. A meticulous examination each method’s technical details follows. This article explores current cutting-edge research trends algorithms, providing perspective their prediction. It investigates utilization algorithms concludes highlighting significant challenges future directions. Emphasis placed key areas such as hydrodynamic coupling, effective data processing acquisition, mitigating model uncertainty. paper provides detailed present state principal characteristics emerging technologies

Язык: Английский

Predicting Water Potability: Leveraging Machine Learning Techniques

Опубликована: Май 17, 2024

Язык: Английский

Water Quality Evaluation using Machine Learning

2022 7th International Conference on Communication and Electronics Systems (ICCES), Год журнала: 2024, Номер unknown, С. 754 - 758

Опубликована: Дек. 16, 2024

Язык: Английский