A survey on river water quality modelling using artificial intelligence models: 2000–2020

TM Tung, ZM Yaseen - Journal of Hydrology, 2020 - Elsevier
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 …

A review of the artificial neural network models for water quality prediction

Y Chen, L Song, Y Liu, L Yang, D Li - Applied Sciences, 2020 - mdpi.com
Water quality prediction plays an important role in environmental monitoring, ecosystem
sustainability, and aquaculture. Traditional prediction methods cannot capture the nonlinear …

Exploring the application of artificial intelligence technology for identification of water pollution characteristics and tracing the source of water quality pollutants

P Wang, J Yao, G Wang, F Hao, S Shrestha… - Science of the Total …, 2019 - Elsevier
Point sources are important routes through which pollutants enter rivers. It is important to
identify the characteristics of and trace the origins of water pollutants. In this study, an …

Uncertainty assessment of the multilayer perceptron (MLP) neural network model with implementation of the novel hybrid MLP-FFA method for prediction of …

B Raheli, MT Aalami, A El-Shafie, MA Ghorbani… - Environmental Earth …, 2017 - Springer
Accurate prediction of the chemical constituents in major river systems is a necessary task
for water quality management, aquatic life well-being and the overall healthcare planning of …

Evaluating the water quality characteristics and tracing the pollutant sources in the Yellow River Basin, China

Y Tian, Z Wen, M Cheng, M Xu - Science of The Total Environment, 2022 - Elsevier
Evaluating water quality characteristics (WQC) and tracing pollutant sources (PS) have
gradually attracted worldwide attention. This study was conducted to develop an integrated …

A review of water quality models and monitoring methods for capabilities of pollutant source identification, classification, and transport simulation

P Talukdar, B Kumar, VV Kulkarni - Reviews in Environmental Science …, 2023 - Springer
Water quality monitoring and modeling are vital in improving the aquatic ecosystem's health
and surroundings. The advancements in computer science and its integration with …

Quality assessment and artificial neural networks modeling for characterization of chemical and physical parameters of potable water

M Salari, ES Shahid, SH Afzali, M Ehteshami… - Food and Chemical …, 2018 - Elsevier
Today, due to the increase in the population, the growth of industry and the variety of
chemical compounds, the quality of drinking water has decreased. Five important river water …

Estimation of nitrate concentration in groundwater of Kadava river basin-Nashik district, Maharashtra, India by using artificial neural network model

VM Wagh, DB Panaskar, AA Muley - Modeling earth systems and …, 2017 - Springer
Monitoring of groundwater quality is an important tool to facilitating adequate information
about water management in respective areas. Nitrate concentration in aquifer systems is …

Evolving genetic programming and other AI-based models for estimating groundwater quality parameters of the Khezri plain, Eastern Iran

A Aryafar, V Khosravi, H Zarepourfard… - Environmental earth …, 2019 - Springer
Genetic programming (GP) was used to determine relationships between groundwater
quality parameters including total hardness (TH), total dissolved solids (TDS) and electrical …

Evaluating physical and fiscal water leakage in water distribution system

SK Bhagat, Tiyasha, W Welde, O Tesfaye, TM Tung… - Water, 2019 - mdpi.com
With increasing population, the need for research ideas on the field of reducing wastage of
water can save a big amount of water, money, time, and energy. Water leakage (WL) is an …