… Machine learning algorithms are used in this work to predict water quality index (WQI) and
water quality classification … of the machine learning techniques in the next section to predict …

… texture analysis with artificial intelligence or machine learning (ML) algorithms might … based
computed tomography (CT) texture analysis to distinguish benign and malignant renal solid …

… is to examine machine learning algorithms utilized in … most recent advances in
recycling-related machine learning. … A community’s refuse is a type of municipal solid waste (MSW…

… concept, ensemble learning, has … the ensemble learning techniques is to combine predictions
of multiple ML techniques using different voting systems in order to attain better predictive …

… [32] adopted a machine learning approach to predict the mechanical … a machine learning
based approach accounting for uncertainties to assist stochastic modeling and finally predict …

… This study investigated the machine learning performance of approaches as a result of XGB,
RF, SVC, ADA, and Decision Trees in predicting the components of a water quality dataset. …

… Herein, we present a machine learning-based alloy design system (MADS) to facilitate the …
Furtherly, a hardness prediction model based on the support vector machine was constructed …

… In this study, the best features are selected by the RFE method, and the three machine
learning models of StoGB, RotFor, and Bayesglm showed promising results in the prediction of …

… approach. In this research paper, we are presenting a comparative analysis of popular
machine learning-based … We have used seven machine learning-based classifiers. These …

… In this study, machine learning approach was applied on two vertical flow constructed wetland
having different media ie, expanded clay and biochar, to have the understanding of critical …