A model for prediction of monthly solar radiation of different meterological locations of Bangladesh using aritficial neural network data mining tool
2017 International Conference on Electrical, Computer and Communication Engineering (ECCE), 2017
Solar energy generated by the sunlight is non schedulable due to the stochastic behavior of meteo... more Solar energy generated by the sunlight is non schedulable due to the stochastic behavior of meteorological conditions. Also the equipment for measuring the solar irradiance is expensive and rarely available in all locations of the globe. Hence prior knowledge of solar radiation is very important, for better management, sizing and control of solar energy installations. Predictive data mining such as Artificial Neural Network (ANN) is one of the most reliable and accurate model for forecasting solar radiation. There are a number of meteorological and geographical parameters which affect the solar radiation prediction model. So, identification of most influential parameters for better prediction accuracy is a crucial factor. In this paper, three attribute evaluators of Waikato Environment for Knowledge Analysis (WEKA) such as Classifier Subset Eval, CFS Subset Eval and Wrapper Subset Eval are used to select the most influential input parameters for ANN model for prediction of solar rad...
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Papers by Riku Chowdhury