2021
DOI: 10.1016/j.rser.2020.110114
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Prediction of daily global solar radiation using different machine learning algorithms: Evaluation and comparison

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Cited by 268 publications
(95 citation statements)
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References 77 publications
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“…One of the key features of ML is a training model using different dependent and independent attributes, which further depends on the type of learning algorithm (supervised, semisupervised, or unsupervised). ML algorithms are widely used for prediction purposes and applied to provide solutions to questions such as global solar radiation [9], accuracy in determining the mortality rate in COVID-19 patients [10], and efficient processes for manufacturing industries [11]. In addition, ML algorithms assist the educational sector to evaluate student performance [12], forecast student dropout rates in any course [13], and understand students' unique learning styles [14].…”
Section: Introductionmentioning
confidence: 99%
“…One of the key features of ML is a training model using different dependent and independent attributes, which further depends on the type of learning algorithm (supervised, semisupervised, or unsupervised). ML algorithms are widely used for prediction purposes and applied to provide solutions to questions such as global solar radiation [9], accuracy in determining the mortality rate in COVID-19 patients [10], and efficient processes for manufacturing industries [11]. In addition, ML algorithms assist the educational sector to evaluate student performance [12], forecast student dropout rates in any course [13], and understand students' unique learning styles [14].…”
Section: Introductionmentioning
confidence: 99%
“…If MBE value is positive, then it means that mean of predicted values is higher than that of actual values. If it is negative, it means that mean of predicted values is smaller than that of actual values [22]. With this viewpoint, all results in terms of MBE metric are positive and varied from 0.014 to 1.1356 (See Table 4).…”
Section: Resultsmentioning
confidence: 94%
“…These are R 2 , RMSE and MBE. Table 3 gives the equations and desired cases of these metrics [19,21,22]. Table 3.…”
Section: Evaluation Metricsmentioning
confidence: 99%
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“…A review of solar irradiance forecasting using four different machine learning techniques (artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor (k-NN), and deep learning (DL)) are presented in [61]. The comparison between the different techniques identified that ANN algorithm provided the best fitting for the data, followed by the DL, SVM, and k-NN techniques.…”
Section: Ai For Solar Irradiance Forecastingmentioning
confidence: 99%