Water quality prediction and classification based on principal component regression and gradient boosting classifier approach

Robust Machine Learning Algorithms for Predicting Coastal Water Quality Index

“…Compared with other algorithms like SVM and KNN, the DT provides better results that are effective for the prediction (Huynh-Cam et al, 2021). Unlike the Recently, several studies have also revealed that the XGB algorithm is effective for predicting WQIs (Grbčić et al, 2021;Huan et al, 2020;Islam Khan et al, 2021;Uddin et al, 2022b). Because the ensemble based algorithms combine multiple DTs and consider the average of the output of all DTs for the prediction (Malek et al, 2022).…”

“…They suggest that tree-based algorithms are practical for predicting WQIs. Some studies recommend that ensemble tree-based algorithms such as extreme gradient boosting (XGB) and random forest (RF) are potentially useful for predicting WQIs (Grbčić et al, 2021;Haghiabi et al, 2018a;Islam Khan et al, 2021;Khullar and Singh, 2021). Moreover, researchers successfully applied AI-based algorithms like support vector machine (SVM), least square SVM (LSVM) and artificial neural network for predicting WQIs (Aldhyani et al, 2020;Haghiabi et al, 2018b;Pham et al, 2019;Prasad et al, 2022;Wu and Wang, 2022).…”

Performance analysis of the water quality index model for predicting water state using machine learning techniques

“…After obtaining the water quality classes, the WQI models performance were evaluate utilizing various machine learning classifier algorithms. For the purposes of predicting classification of water quality, recently advanced machine-learning algorithms have widely used to reduce the model uncertainty (Islam Khan et al, 2021;Kaur et al, 2021;Malek et al, 2022;Najafzadeh et al, 2019;Najafzadeh and Ghaemi, 2019). Recently, a few studies have utilized the machine learning technique in order to assess the WQI model's reliability in terms of predicting the correct classification of water quality (Islam Khan et al, 2021;.…”

“…For the purposes of predicting classification of water quality, recently advanced machine-learning algorithms have widely used to reduce the model uncertainty (Islam Khan et al, 2021;Kaur et al, 2021;Malek et al, 2022;Najafzadeh et al, 2019;Najafzadeh and Ghaemi, 2019). Recently, a few studies have utilized the machine learning technique in order to assess the WQI model's reliability in terms of predicting the correct classification of water quality (Islam Khan et al, 2021;. Up to date, most machine learning algorithms has developed for the solution of binary classification (Allwein, 2000;Babbar and Babbar, 2017).…”

Vertical Electric Sounding and Multi-Layered Deming Perceptive Classifier for Ground Water Identification and Quality Prediction Analysis

“…However, prediction time is not reduced with hybrid scheme. Water quality prediction scheme is developed in [10] with regression method. WQI was determined with arithmetic index technique.…”