… prediction model based on single machine learning algorithms need to be improved, and
the hybrid prediction … The objective of this study was to obtain the most accurate prediction of …

… The main aim of this work was to compare six machine learning (ML) - based models to
predict the municipal solid waste (MSW) generation from selected residential areas of Vietnam. …

… method. This study proposes a novel application of ensemble learning that incorporates
several intelligent ensemble members into an integrated model by means of majority voting. The …

… The results obtained indicate that the prediction ability of the random forests DM model is
superior to the other ensemble learners, followed by the ensemble Bag-CHAID method. On …

… This paper presents a novel dynamic ensemble learning (DEL) algorithm for designing
ensemble of neural networks (NNs). DEL algorithm determines the size of ensemble, the number …

… ), a simple and fast method for obtaining its compositional information. The spectral data
produced by this technique can be explored using machine learning methods, such as neural …

… ensemble machine learning (ML) model for prediction … ensemble ML model’s prediction
performance was compared with five commonly-used ML models. It is shown that the ensemble …

… prediction results with different models, including benchmark smart persistence and traditional
machine learning … In this paper, a new approach for estimating hourly GHI is developed …

… and implementing ensemble learning strategies over individual learning models to predict
the … the individual and ensemble machine learning approaches for HPC prediction. The …

… ensemble machine learning … predicting the wastewater effluent parameters (eg, BOD 5 ,
COD, TDS). The main aim of this research is to assess the performance of the ensemble learning …