Calculation of Solar Radiation by Using Regression Methods

International Physics Conference at the Anatolian Peak 2016

Kiziltan, Ö.^1 ; Sahin, M.^1

Electrical and Electronic Engineering, Engineering Faculty, Siirt University, Siirt

56100, Turkey^1

关键词: Climatic conditions;    Correlation coefficient;    Gaussian process regression;    Land surface temperature;    National Oceanic and Atmospheric Administration;    Regression coefficient;    Regression method;    Root mean square errors;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/707/1/012049/pdf
DOI  :  10.1088/1742-6596/707/1/012049

来源: IOP

【 摘 要 】

In this study, solar radiation was estimated at 53 location over Turkey with varying climatic conditions using the Linear, Ridge, Lasso, Smoother, Partial least, KNN and Gaussian process regression methods. The data of 2002 and 2003 years were used to obtain regression coefficients of relevant methods. The coefficients were obtained based on the input parameters. Input parameters were month, altitude, latitude, longitude and landsurface temperature (LST).The values for LST were obtained from the data of the National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite. Solar radiation was calculated using obtained coefficients in regression methods for 2004 year. The results were compared statistically. The most successful method was Gaussian process regression method. The most unsuccessful method was lasso regression method. While means bias error (MBE) value of Gaussian process regression method was 0,274 MJ/m2, root mean square error (RMSE) value of method was calculated as 2,260 MJ/m2. The correlation coefficient of related method was calculated as 0,941. Statistical results are consistent with the literature. Used the Gaussian process regression method is recommended for other studies.