A survey on river water quality modelling using artificial intelligence models: 2000–2020
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 …
anthropogenic activities. Last decades' research has immensely focussed on river basin …
Predicting water quality with artificial intelligence: a review of methods and applications
D Irwan, M Ali, AN Ahmed, G Jacky, A Nurhakim… - … Methods in Engineering, 2023 - Springer
The water is the main pivotal sources of irrigation in agricultural activities and affects human
daily activities such as drinking. The water quality has a significant impact on various …
daily activities such as drinking. The water quality has a significant impact on various …
Prediction of irrigation groundwater quality parameters using ANN, LSTM, and MLR models
Forecasting the irrigation groundwater parameters helps plan irrigation water and crop, and
it is commonly expensive because it needs various parameters, mainly in develo** …
it is commonly expensive because it needs various parameters, mainly in develo** …
[HTML][HTML] Water quality prediction and classification based on principal component regression and gradient boosting classifier approach
Estimating water quality has been one of the significant challenges faced by the world in
recent decades. This paper presents a water quality prediction model utilizing the principal …
recent decades. This paper presents a water quality prediction model utilizing the principal …
Predicting Water Quality Index (WQI) by feature selection and machine learning: A case study of An Kim Hai irrigation system
A variety of water quality indices have been used to assess the state of waterbodies all over
the world. In calculating a Water Quality Index (WQI), traditional methods require the …
the world. In calculating a Water Quality Index (WQI), traditional methods require the …
Water quality prediction using SWAT-ANN coupled approach
Efficient and accurate prediction of river water quality is challenging due to the complex
hydrological and environmental processes affecting their nature. The challenge is even …
hydrological and environmental processes affecting their nature. The challenge is even …
Mixed coagulant-flocculant optimization for pharmaceutical effluent pretreatment using response surface methodology and Gaussian process regression
Abstract Wastewater from the Antibiotical-Saidal pharmaceutical plant (Medéa) was
pretreated by coagulation-flocculation using copper sulfate (CuSO 4), iron chloride (FeCl 3) …
pretreated by coagulation-flocculation using copper sulfate (CuSO 4), iron chloride (FeCl 3) …
Approach based on TOPSIS and Monte Carlo simulation methods to evaluate lake eutrophication levels
This study presents an approach for eutrophication evaluation based on the technique for
order preference by similarity to an ideal solution (TOPSIS) method and Monte Carlo …
order preference by similarity to an ideal solution (TOPSIS) method and Monte Carlo …
Prediction of long-term water quality using machine learning enhanced by Bayesian optimisation
Water quality assessment is critical to better recognise the importance of water in human
society. In this study, a new framework to predict long-term water quality is proposed by …
society. In this study, a new framework to predict long-term water quality is proposed by …
An improved adaptive neuro fuzzy inference system model using conjoined metaheuristic algorithms for electrical conductivity prediction
Precise prediction of water quality parameters plays a significant role in making an early
alert of water pollution and making better decisions for the management of water resources …
alert of water pollution and making better decisions for the management of water resources …