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Performance of Neural Wavelet and ANFIS Algorithms for Short-Term Prediction of Solar Radiation and Wind Velocities
* 1 , 1 , 2 , 3 , 4
1  Young Researchers and Elite Club, South Tehran Branch, Islamic Azad University, Tehran, Iran
2  Department of Mechanical and Aerospace Engineering, Syracuse University, USA
3  Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada
4  Islamic Azad University, South Tehran Branch, School of Industrial Engineering, P.O. Box 1151863411, Tehran, Iran

Published: 03 November 2014 by MDPI in The 4th World Sustainability Forum session Energy Sustainability
Abstract: Prediction of wind and solar energy is deemed one of the most important contributory factors towards sustainability. Along the same lines, to harvest energy and guarantee the safety of a place, accurate information about the future of the region is needed. To achieve the target, this paper predicts solar irradiation and wind velocity time series by two robust artificial intelligence algorithms which are called Wavelet and ANFIS (Adaptive Network Fuzzy Inference System). The data used for the predictor system are obtained from a meteorological station in Tehran, Iran.  The results show that a) robustness of both algorithms for prediction of wind velocities and solar irradiation b) superior strength of Wavelet to ANFIS for prediction of solar irradiation c) ANFIS makes a better prediction of Wavelet for wind velocities.
Keywords: Neural wavelet, ANFIS, Solar radiation, wind velocity, Iran, Artificial Intelligence