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Application of Neural Networks and Lifting Wavelet Transform for Long Term Solar Radiation Prediction

Publication Type : Book Chapter

Publisher : Springer

Source : Advances in Cybernetics, Cognition, and Machine Learning for Communication Technologies, Springer, Pg 95-105,2020

Url : https://link.springer.com/chapter/10.1007/978-981-15-3125-5_11

Campus : Bengaluru

School : School of Computing

Department : Computer Science

Year : 2020

Abstract : In the past research scholars, have tried to predict solar radiation for a short duration for power prediction. However, with increase in applications requiring predicted data for solar radiation need for long duration prediction has increased. Present work carried out by application of concurrent Neural Networks and lifting wavelet transform for long-term power prediction. A brief review of Neural Networks and second-generation wavelets carried out for their application in long-term solar radiation power generation. Algorithm developed and experiments conducted with results presented for long-term prediction of solar radiation. Results produced present quite accurate prediction for a duration up to three months.

Cite this Research Publication : Manju Khanna, N. K. Srinath, J. K. Mendiratta , "Application of Neural Networks and Lifting Wavelet Transform for Long Term Solar Radiation Prediction", Advances in Cybernetics, Cognition, and Machine Learning for Communication Technologies, Springer, Pg 95-105,2020

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