2017 International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS) 2017
DOI: 10.1109/wits.2017.7934658
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A review of solar radiation prediction using artificial neural networks

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Cited by 19 publications
(10 citation statements)
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“…where Gmeas is the measured value of the solar radiation and Gpred is the estimated value of the solar radiation. R 2 is selected as it is one of the most frequently used parameters to measure the accuracy of solar radiation prediction [9]. Therefore, by calculating the R 2 , the accuracy of the proposed method could easily be compared with the accuracy of the methods from previous studies.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…where Gmeas is the measured value of the solar radiation and Gpred is the estimated value of the solar radiation. R 2 is selected as it is one of the most frequently used parameters to measure the accuracy of solar radiation prediction [9]. Therefore, by calculating the R 2 , the accuracy of the proposed method could easily be compared with the accuracy of the methods from previous studies.…”
Section: Resultsmentioning
confidence: 99%
“…Various methods have been proposed to estimate either the daily average or hourly solar radiation. The artificial neural network (ANN) method for estimation is one of the most popular methods for the daily average prediction due to its high accuracy [9,10]. While a wider range of methods has been used to estimate hourly solar radiation, ANN-based methods have also been applied with accurate results.…”
Section: Introductionmentioning
confidence: 99%
“…This can be achieved by utilizing artificial neural networks (ANN) because of their ability to learn and train the system model. Artificial neural networks make a computational model to simulate nonlinear, complex, and time-varying systems [7].…”
Section: Artificial Neural Networkmentioning
confidence: 99%
“…Recent methods employ machine learning algorithm in the form of artificial neural network (ANN) [18]- [20], gradient boosting tree (GBT) [21], genetic programming (GP) [22], [23], and support vector machine [24], [25] among others. In comparison with other estimation method,multi-layer perceptron ANN is one of the most popular since it solves high non-linearity, complex, and time-varying problems [26] and it has also been proven to have higher accuracy [27], [28].…”
Section: Introductionmentioning
confidence: 99%