jpr.4.2.13723
Short-term Solar Irradiance Forecasting Using Different Artificial Neural Network Algorithms
Sanjay Kumar Prajapati
Mukh Raj Yadav
Kishan Bhushan Sahay
Journal on Pattern Recognition
2350-112X
4
2
1
9
10.26634/jpr.4.2.13723
Information Compression, Predictive Analysis, Artificial Neural Network, Data Analysis
The expectation of sun oriented radiation is essential for a few applications in renewable vitality research. There are various land variables, which influence sun powered radiation forecast, the recognizable proof of these variables for precise sun powered radiation expectation is vital. This paper explores a mixture strategy for the pressure of sun powered radiation utilizing prescient investigation. The forecast of moment insightful sun oriented radiation is performed by utilizing diverse models of Artificial Neural Networks (ANN), to be specific Multi-Layer Perceptron Neural System (MLPNN), Levenberg-Marquardt, Scaled Conjugate Gradient. Root Mean Square Error (RMSE) is utilized to assess the forecast precision of the three ANN models utilized. The data and information picked up from the present study could enhance the precision of examination concerning atmosphere studies and help in blockage control.
June - August 2017
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