There has been an unsettling rise in the river contamination due to the climate change and
anthropogenic activities. Last decades' research has immensely focussed on river basin …

Neuro-fuzzy systems have attracted the growing interest of researchers in various scientific
and engineering areas due to its effective learning and reasoning capabilities. The neuro …

Adaptive Neuro‐Fuzzy Inference System (ANFIS) blends advantages of both Artificial Neural
Networks (ANNs) and Fuzzy Logic (FL) in a single framework. It provides accelerated …

The goal of this paper was to conduct a systematic literature analysis on the application of
different types of artificial intelligence models in surface water quality monitoring. The …

An accurate prediction of water quality (WQ) related parameters is considered as pivotal
decisive tool in sustainable water resources management. In this study, five different …

Modeling surface water quality using artificial intelligence-based models is essential in
projecting suitable mitigation measures. However, it remains a challenge and requires …

Total dissolved solids (TDS) are recognized as an essential indicator of surface water
quality. The current research investigates the potential of a novel computer aid approach …

Prediction of dissolved oxygen (DO) and total dissolved solids (TDS) are of paramount
importance for water environmental protection and analysis of the ecosystem. The traditional …

The quality of water has a direct influence on both human health and the environment. Water
is utilized for a variety of purposes, including drinking, agriculture, and industrial use. The …

In this study, a novel least square support vector machine (LSSVM) model integrated with
gradient-based optimizer (GBO) algorithm is introduced for the assessment of water quality …