Today, various methods have been developed to extract drinking water resources, which
scientists use to simulate the quantitative and qualitative water resources parameters. Due …

Artificial neural networks (ANNs) could be used in effective drinking water quality
management. This review provides an overview about the history of ANNs and their …

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 …

Dissolved oxygen (DO) is an important indicator reflecting the healthy state of aquatic
ecosystems. The balance between oxygen supply and consuming in the water body is …

In recent years, as a result of climate change as well as rainfall reduction in arid and semi‐
arid regions, modelling qualitative and quantitative parameters belonging to aquifers has …

In this study, performance of two artificial networks was evaluated to determine which one
would have more efficiency in predicting nitrate contamination of groundwater. The case …

Rationalization of water quality monitoring stations nowadays is applied in many countries.
In some cases, missing data from abandoned/inactive stations, spatial and temporal, could …

Precise prediction of the water quality time series may provide directions for early warning of
water pollution and help policymakers to manage water resources more effectively. This …

River water quality monitoring using traditional water sampling and laboratory analyses is
expensive and time-consuming. The application of artificial neural network (ANN) models to …

In the world's water scarce regions, groundwater as an important and strategic resource
needs proper assessment. An accurate forecasting needs to be performed in order to make …