PSO-NN-Based Hybrid Model for Long-Term Wind Speed Prediction: A Study on 67 Cities of India
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Publisher
Springer Singapore
Link
http://link.springer.com/content/pdf/10.1007/978-981-13-1822-1_29
Reference20 articles.
1. Indian Wind Energy Association, http://www.inwea.org/ . Accessed 10 Nov 2017
2. Azad, H.B., Mekhilef, S., Ganapathy, V.G.: Long-term wind speed forecasting and general pattern recognition using neural networks. IEEE Trans. Sustain. Energy 5(2), 546–553 (2014)
3. Brkaa, A., Al-Abdeli, Y.M., Kothapalli, G.: Influence of neural network training parameters on short-term wind forecasting. Int. J. Sustain. Energy (2014)
4. Huang, C.-M., Kuo, C.-J., Huang, Y.-C.: Short-term wind power forecasting and uncertainty analysis using a hybrid intelligent method. IET Renew. Power Gener. 11(5), 678–687 (2017)
5. Haque, A.U., Mandal, P., Meng, J., Negnevitsky, M.: Wind speed forecast model for wind farm based on a hybrid machine learning algorithm. Int. J. Sustain. Energy, 34(1), 38–51 (2015)
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