The Experts below are selected from a list of 279 Experts worldwide ranked by ideXlab platform
Ismail Daut - One of the best experts on this subject based on the ideXlab platform.
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Linear Regression Model in Estimating Solar Radiation in Perlis
Energy Procedia, 2012Co-Authors: Safwati Ibrahim, Ismail Daut, Yusoff Mohd Irwan, Muhammad Irwanto, N. Gomesh, Z. FarhanaAbstract:AbstractStatistical models for predicting the Solar Radiation have been developed. In any prediction of the Solar Radiation, an understanding of its characteristics is of fundamental importance. This study presents an investigation of a relationship between Solar Radiation and temperature in Perlis, Northern Malaysia for the year of 2006. To achieve this, the data are presented in daily averaged maximum and minimum air temperature, and daily averaged Solar Radiation. Since the scatter plots represent the straight line, the linear regression model was selected to estimate the Solar Radiation. It was found that the linear correlation coefficient value is 0.7473 shows that a strong linear relationship between Solar Radiation and temperature. The analysis of variance R2 is 0.5585 that is; about 56 percent of the variability in temperature is accounted for by the straight-line fit to Solar Radiation. Based on the results, the fitted model is adequate to represent the estimation of Solar Radiation
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An Estimation of Solar Radiation using Robust Linear Regression Method
Energy Procedia, 2012Co-Authors: Siti Fatimah Ibrahim, Ismail Daut, Yusoff Mohd Irwan, Muhammad Irwanto, N. Gomesh, A.r.n. RazlianaAbstract:Abstract The air temperature data is the most important component to estimate the Solar Radiation in photovoltaic systems. From the Malaysia Meteorological Department, the data of air temperature and Solar Radiation can be found the hourly, daily, monthly and also the annually. Based on Solar Radiation data for the past 26 years, the average monthly Solar Radiation was 5009.56 Wh/m2. It was greater than the normal Solar Radiation (3 kWh/m2), which indicates that the sky in Perlis was clear and very high Solar Radiation intensity for the months in the past 26 years. This paper presents an investigation of a relationship between Solar Radiation and temperature in Perlis, Northern Malaysia for the year of 2006. The Least Trimmed Squares (LTS) robust regression model was selected to estimate the Solar Radiation since the robust method is do not breakdown easily and are not much influenced by outliers.
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Relationship between the Solar Radiation and Surface Temperature in Perlis
Advanced Materials Research, 2012Co-Authors: Ismail Daut, Safwati Ibrahim, Muhammad Irwanto, Mohd Irwan Yusoff, Gomesh NsurfaceAbstract:Statistical models for predicting the Solar Radiation have been developed. In any prediction of the Solar Radiation, an understanding of its characteristics is of fundamental importance. This study presents an investigation of a relationship between Solar Radiation and surface temperature in Perlis, Northern Malaysia for the year of 2006. To achieve this, the data are presented in daily averaged maximum and minimum surface temperature, and daily averaged Solar Radiation. Since the scatter plots represent the straight line, the linear regression model was selected to estimate the Solar Radiation. It was found that the linear correlation coefficient value is 0.7473 shows that a strong linear relationship between Solar Radiation and surface temperature. The analysis of variance R2 is 0.5585 that is; about 56 percent of the variability in temperature is accounted for by the straight-line fit to Solar Radiation. Based on the results, the fitted model is adequate to represent the estimation of Solar Radiation.
Muhammad Irwanto - One of the best experts on this subject based on the ideXlab platform.
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Linear Regression Model in Estimating Solar Radiation in Perlis
Energy Procedia, 2012Co-Authors: Safwati Ibrahim, Ismail Daut, Yusoff Mohd Irwan, Muhammad Irwanto, N. Gomesh, Z. FarhanaAbstract:AbstractStatistical models for predicting the Solar Radiation have been developed. In any prediction of the Solar Radiation, an understanding of its characteristics is of fundamental importance. This study presents an investigation of a relationship between Solar Radiation and temperature in Perlis, Northern Malaysia for the year of 2006. To achieve this, the data are presented in daily averaged maximum and minimum air temperature, and daily averaged Solar Radiation. Since the scatter plots represent the straight line, the linear regression model was selected to estimate the Solar Radiation. It was found that the linear correlation coefficient value is 0.7473 shows that a strong linear relationship between Solar Radiation and temperature. The analysis of variance R2 is 0.5585 that is; about 56 percent of the variability in temperature is accounted for by the straight-line fit to Solar Radiation. Based on the results, the fitted model is adequate to represent the estimation of Solar Radiation
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An Estimation of Solar Radiation using Robust Linear Regression Method
Energy Procedia, 2012Co-Authors: Siti Fatimah Ibrahim, Ismail Daut, Yusoff Mohd Irwan, Muhammad Irwanto, N. Gomesh, A.r.n. RazlianaAbstract:Abstract The air temperature data is the most important component to estimate the Solar Radiation in photovoltaic systems. From the Malaysia Meteorological Department, the data of air temperature and Solar Radiation can be found the hourly, daily, monthly and also the annually. Based on Solar Radiation data for the past 26 years, the average monthly Solar Radiation was 5009.56 Wh/m2. It was greater than the normal Solar Radiation (3 kWh/m2), which indicates that the sky in Perlis was clear and very high Solar Radiation intensity for the months in the past 26 years. This paper presents an investigation of a relationship between Solar Radiation and temperature in Perlis, Northern Malaysia for the year of 2006. The Least Trimmed Squares (LTS) robust regression model was selected to estimate the Solar Radiation since the robust method is do not breakdown easily and are not much influenced by outliers.
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Relationship between the Solar Radiation and Surface Temperature in Perlis
Advanced Materials Research, 2012Co-Authors: Ismail Daut, Safwati Ibrahim, Muhammad Irwanto, Mohd Irwan Yusoff, Gomesh NsurfaceAbstract:Statistical models for predicting the Solar Radiation have been developed. In any prediction of the Solar Radiation, an understanding of its characteristics is of fundamental importance. This study presents an investigation of a relationship between Solar Radiation and surface temperature in Perlis, Northern Malaysia for the year of 2006. To achieve this, the data are presented in daily averaged maximum and minimum surface temperature, and daily averaged Solar Radiation. Since the scatter plots represent the straight line, the linear regression model was selected to estimate the Solar Radiation. It was found that the linear correlation coefficient value is 0.7473 shows that a strong linear relationship between Solar Radiation and surface temperature. The analysis of variance R2 is 0.5585 that is; about 56 percent of the variability in temperature is accounted for by the straight-line fit to Solar Radiation. Based on the results, the fitted model is adequate to represent the estimation of Solar Radiation.
N. Gomesh - One of the best experts on this subject based on the ideXlab platform.
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Linear Regression Model in Estimating Solar Radiation in Perlis
Energy Procedia, 2012Co-Authors: Safwati Ibrahim, Ismail Daut, Yusoff Mohd Irwan, Muhammad Irwanto, N. Gomesh, Z. FarhanaAbstract:AbstractStatistical models for predicting the Solar Radiation have been developed. In any prediction of the Solar Radiation, an understanding of its characteristics is of fundamental importance. This study presents an investigation of a relationship between Solar Radiation and temperature in Perlis, Northern Malaysia for the year of 2006. To achieve this, the data are presented in daily averaged maximum and minimum air temperature, and daily averaged Solar Radiation. Since the scatter plots represent the straight line, the linear regression model was selected to estimate the Solar Radiation. It was found that the linear correlation coefficient value is 0.7473 shows that a strong linear relationship between Solar Radiation and temperature. The analysis of variance R2 is 0.5585 that is; about 56 percent of the variability in temperature is accounted for by the straight-line fit to Solar Radiation. Based on the results, the fitted model is adequate to represent the estimation of Solar Radiation
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An Estimation of Solar Radiation using Robust Linear Regression Method
Energy Procedia, 2012Co-Authors: Siti Fatimah Ibrahim, Ismail Daut, Yusoff Mohd Irwan, Muhammad Irwanto, N. Gomesh, A.r.n. RazlianaAbstract:Abstract The air temperature data is the most important component to estimate the Solar Radiation in photovoltaic systems. From the Malaysia Meteorological Department, the data of air temperature and Solar Radiation can be found the hourly, daily, monthly and also the annually. Based on Solar Radiation data for the past 26 years, the average monthly Solar Radiation was 5009.56 Wh/m2. It was greater than the normal Solar Radiation (3 kWh/m2), which indicates that the sky in Perlis was clear and very high Solar Radiation intensity for the months in the past 26 years. This paper presents an investigation of a relationship between Solar Radiation and temperature in Perlis, Northern Malaysia for the year of 2006. The Least Trimmed Squares (LTS) robust regression model was selected to estimate the Solar Radiation since the robust method is do not breakdown easily and are not much influenced by outliers.
Yusoff Mohd Irwan - One of the best experts on this subject based on the ideXlab platform.
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Linear Regression Model in Estimating Solar Radiation in Perlis
Energy Procedia, 2012Co-Authors: Safwati Ibrahim, Ismail Daut, Yusoff Mohd Irwan, Muhammad Irwanto, N. Gomesh, Z. FarhanaAbstract:AbstractStatistical models for predicting the Solar Radiation have been developed. In any prediction of the Solar Radiation, an understanding of its characteristics is of fundamental importance. This study presents an investigation of a relationship between Solar Radiation and temperature in Perlis, Northern Malaysia for the year of 2006. To achieve this, the data are presented in daily averaged maximum and minimum air temperature, and daily averaged Solar Radiation. Since the scatter plots represent the straight line, the linear regression model was selected to estimate the Solar Radiation. It was found that the linear correlation coefficient value is 0.7473 shows that a strong linear relationship between Solar Radiation and temperature. The analysis of variance R2 is 0.5585 that is; about 56 percent of the variability in temperature is accounted for by the straight-line fit to Solar Radiation. Based on the results, the fitted model is adequate to represent the estimation of Solar Radiation
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An Estimation of Solar Radiation using Robust Linear Regression Method
Energy Procedia, 2012Co-Authors: Siti Fatimah Ibrahim, Ismail Daut, Yusoff Mohd Irwan, Muhammad Irwanto, N. Gomesh, A.r.n. RazlianaAbstract:Abstract The air temperature data is the most important component to estimate the Solar Radiation in photovoltaic systems. From the Malaysia Meteorological Department, the data of air temperature and Solar Radiation can be found the hourly, daily, monthly and also the annually. Based on Solar Radiation data for the past 26 years, the average monthly Solar Radiation was 5009.56 Wh/m2. It was greater than the normal Solar Radiation (3 kWh/m2), which indicates that the sky in Perlis was clear and very high Solar Radiation intensity for the months in the past 26 years. This paper presents an investigation of a relationship between Solar Radiation and temperature in Perlis, Northern Malaysia for the year of 2006. The Least Trimmed Squares (LTS) robust regression model was selected to estimate the Solar Radiation since the robust method is do not breakdown easily and are not much influenced by outliers.
S S Chandel - One of the best experts on this subject based on the ideXlab platform.
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Solar Radiation prediction using artificial neural network techniques a review
Renewable & Sustainable Energy Reviews, 2014Co-Authors: Amit Kumar Yadav, S S ChandelAbstract:Abstract Solar Radiation data plays an important role in Solar energy research. These data are not available for location of interest due to absence of a meteorological station. Therefore, the Solar Radiation has to be predicted accurately for these locations using various Solar Radiation estimation models. The main objective of this study is to review Artificial Neural Network (ANN) based techniques in order to identify suitable methods available in the literature for Solar Radiation prediction and to identify research gaps. The study shows that Artificial Neural Network techniques predict Solar Radiation more accurately in comparison to conventional methods. The prediction accuracy of ANN models is found to be dependent on input parameter combinations, training algorithm and architecture configurations. Further research areas in ANN technique based methodologies are also identified in the present study.