A Novel Model Based on Square Root Elastic Net and Artificial Neural Network for Forecasting Global Solar Radiation
In recent years, solar energy has attracted a great deal of attentions from scientific researchers because it is a clean and renewable form of energy. To make good use of solar energy, an effective way to forecast solar radiation is essential to guarantee the reliability of grid-connected photovolta...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/8135193 |
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| _version_ | 1849404093454352384 |
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| author | He Jiang Yao Dong |
| author_facet | He Jiang Yao Dong |
| author_sort | He Jiang |
| collection | DOAJ |
| description | In recent years, solar energy has attracted a great deal of attentions from scientific researchers because it is a clean and renewable form of energy. To make good use of solar energy, an effective way to forecast solar radiation is essential to guarantee the reliability of grid-connected photovoltaic installations. Although an artificial neural network (ANN) is of great importance, irrelevant variables are utilized which results in complex model and intractable computation cost. To remove these irrelevant variables, the combination of variable selection methods and ANN are applied. However, how to select the regularization parameters in these techniques is challenging. This paper successfully investigates a square root elastic net- (SREN-) based approach to tackle this challenge and selects all the important variables. An Elman neural network (ENN) is constructed with the important variables selected by SREN as inputs. Based on meteorological data, SRENENN has been developed for 1-year period in Xinjiang area of China. The present model delivers superior relationship between the estimated and measure values. |
| format | Article |
| id | doaj-art-91ada6a19c8c4a21b2a95fbdaa5608ea |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-91ada6a19c8c4a21b2a95fbdaa5608ea2025-08-20T03:37:06ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/81351938135193A Novel Model Based on Square Root Elastic Net and Artificial Neural Network for Forecasting Global Solar RadiationHe Jiang0Yao Dong1School of Statistics, Jiangxi University of Finance and Economics, Nanchang 330013, ChinaSchool of Statistics, Jiangxi University of Finance and Economics, Nanchang 330013, ChinaIn recent years, solar energy has attracted a great deal of attentions from scientific researchers because it is a clean and renewable form of energy. To make good use of solar energy, an effective way to forecast solar radiation is essential to guarantee the reliability of grid-connected photovoltaic installations. Although an artificial neural network (ANN) is of great importance, irrelevant variables are utilized which results in complex model and intractable computation cost. To remove these irrelevant variables, the combination of variable selection methods and ANN are applied. However, how to select the regularization parameters in these techniques is challenging. This paper successfully investigates a square root elastic net- (SREN-) based approach to tackle this challenge and selects all the important variables. An Elman neural network (ENN) is constructed with the important variables selected by SREN as inputs. Based on meteorological data, SRENENN has been developed for 1-year period in Xinjiang area of China. The present model delivers superior relationship between the estimated and measure values.http://dx.doi.org/10.1155/2018/8135193 |
| spellingShingle | He Jiang Yao Dong A Novel Model Based on Square Root Elastic Net and Artificial Neural Network for Forecasting Global Solar Radiation Complexity |
| title | A Novel Model Based on Square Root Elastic Net and Artificial Neural Network for Forecasting Global Solar Radiation |
| title_full | A Novel Model Based on Square Root Elastic Net and Artificial Neural Network for Forecasting Global Solar Radiation |
| title_fullStr | A Novel Model Based on Square Root Elastic Net and Artificial Neural Network for Forecasting Global Solar Radiation |
| title_full_unstemmed | A Novel Model Based on Square Root Elastic Net and Artificial Neural Network for Forecasting Global Solar Radiation |
| title_short | A Novel Model Based on Square Root Elastic Net and Artificial Neural Network for Forecasting Global Solar Radiation |
| title_sort | novel model based on square root elastic net and artificial neural network for forecasting global solar radiation |
| url | http://dx.doi.org/10.1155/2018/8135193 |
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