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|Title:||Assessment and prediction of daily average solar radiation In Chonburi with Neural Network Model|
|Keywords:||Solar Radiation;Cluster Analysis;Neural Network Model|
|Abstract:||Measurements of versatile variables; maximum temperature, minimum temperature, sunshine duration, sea-level pressure, relative humidity, pressure and solar radiation, at Chonburi during 2005 to 2009 were used to assess and build the neural network model for predicting daily average solar radiation. The study results revealed solar radiation and average solar radiation were highest in summer (mid February to mid May) successively in rainy season (mid May to mid October) and winter (mid October to mid February). The days of solar radiation potential were formed into 3 groups by cluster analysis. Cluster 1 represented roughly 6 hours for sunshine duration, 35°C for maximum temperature, 1006 Pa for sea-level pressure and below 70% for relative humidity. Cluster 2 illustrated sunshine duration fluctuated 7 to 11 hours, maximum temperature ranged from 34°C to 37°C, 1007 Pa for sea-level pressure and approximately 70% for relative humidity. Cluster 3 expressed roughly 10 hours for sunshine duration, maximum temperature proximately 33°C, 1008 Pa for sea-level pressure and above 70% for relative humidity.|
|ISSN:||0975-1033 (Online); 0379-5136 (Print)|
|Appears in Collections:||IJMS Vol.47(09) [September 2018]|
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