References
- [1] Global Wind Energy Council (GWEC) [DB/OL].
- [2] J. Z. Wang, Y. L. Song, F. Liu, and R. Hou, “Analysis Application of Forecasting Models in Wind Power Integration: A Review of Multi-Step-Ahead Wind Speed Forecasting Models”, Renewable Sustainable Energy Reviews vol. 60, pp. 960–981, 2016.
- [3] A. Jackson and B. Turnbull, “Identification of Particle-Laden Flow Features from Wavelet Decomposition”, Physica D: Nonlinear Phenomena vol. 361, pp. 12–27, 2016.
- [4] K. Y. Zhang, R. Gencay, and M. E. Yazgan, “Application of Wavelet Decomposition in Time Series Forecasting”, Economics Letters vol. 158, pp. 41–46, 2016.
- [5] V. Gupta and M. Mittal, “KNN PCA Classifier with Autoregressive Modelling During Different ECG Signal Interpretation”, Procedia Computer Science vol. 125, pp. 18–24, 2017.
- [6] E. P. Duff , A. J. Trachtenberg, C. E. Mackay, M. A. Howard, F. Wilson, S. M. Smith, and M. W. Woolrich, “Task-Driven ICA Feature Generation for Accurate Interpretable Prediction using fMRI”, NeuroImage vol. 60, pp. 189–203, Mar 2016.
- [7] J. Naik, P. Satapathy, and P. K. Dash, “Short-Term Wind Speed Wind Power Prediction using Hybrid Empirical Mode Decomposition Kernel Ridge Regression”, Applied Soft Computing, pp. ASOC–4606, 2017.
- [8] L. Y. Liu, D. R. Liu, Q. Sun, H. L. Li, and R. Wennersten, “Forecasting Power Output of Photovoltaic Systemusing a BP Network Method”, Energy Procedia vol. 142, pp. 780–786, 2017.
- [9] J. C. Li, D. L. Zhao, B. F. Ge, K. W. Yang, and Y. W. Chen, “A Link Prediction Method for Heterogeneous Networks Based on BP Neural Network”, Physica A: Statistical Mechanics and its Application vol. 495, pp. 1–17, 2018.
- [10] F. Bre, J. M. Gimenez, and V. D. Fanchinotti, “Prediction of Wind Pressure Coefficients on Building Surfaces using Artificial Neural Networks”, Energy Buildings vol. 158, pp. 1429–1441, 2018.
- [11] R. Rajesh, “Forecasting Supply Chain Resilience Performance using Grey Prediction”, Electronic Commerce Research Applications vol. 20, pp. 42–58, 2016.
- [12] A. Bezuglov and G. Comert, “Short-Term Freeway Traffic Parameter Prediction: Application of Grey System Theory Models”, Expert Systems with Application vol. 62, pp. 284–292, 2016.
- [13] V. Prema and K. Uma Rao, “Development of Statistical Time Series Models for Solar Power Prediction”, Renewable Energy vol. 83, pp. 100–109, 2015.
- [14] Y. N. Zhao, L. Ye, Z. Li, X. R. Song, Y. S. Lang, and J. Su, “A Novel Bidirectional Mechanism Based on Time Series Model for Wind Power Forecasting”, Applied Energy vol, 177, pp. 793–803, 2016.
- [15] A. Khosravi, R. N. N. Koury, L. Machado, and J. J. G. Pabon, “Prediction of Wind Speed Wind Direction using Artificial Neural Network”, Sustainable Energy Technologies Assessments vol. 25, pp. 146–160, 2018.
- [16] S. X. Zhang, Z. P. Zhou, X. M. Chen, Y. Hu, and L. D. Yang, “PDHS-SVM: A Prediction Method for Plant DNase I Hyper-sensitive Sites Based on Support Vector Machine”, Journal of Theoretical Biology vol. 426, pp. 126–133, 2017.
- [17] Y. G. Zhang, J. Y. Yang, K. C. Wang, Z. P. Wang, and Y. D. Wang, “Improved Wind Prediction Based on the Lorenz System”, Renewable Energy vol. 81, pp. 219–226, 2015.
- [18] Y. G. Zhang, P. H. Wang, P. L. Cheng, and S. Lei, “Wind Speed Prediction with Wavelet Time Series Based on Lorenz Disturbance”, Advances in Electrical Computer Engineering vol. 17, pp. 107–114, 2017.
- [19] J. Naik, P. Satapathy, and P. K. Dash, “Short-Term Wind Speed Wind Power Prediction using Hybrid Empirical Mode Decomposition Kernel Ridge Regression”, Applied Soft Computing, pp. ASOC–4606, 2017.
- [20] C. Zhang, H. K. Wei, J. S. Zhao, T. H. Liu, T. T. Zhu, and K. J. Zhang, “Short-Term Wind Speed Forecasting using Empirical Mode Decomposition Feature Selection”, Renewable Energy vol. 96, pp. 727–737, 2016.
- [21] W. Y. Duan, Y. Han, L. M. Huang, B. B. Zhao, and M. H. Wang, “A Hybrid EMD-SVR Model for the Short-Term Prediction of Significant Wave Height”, Ocean Engineering, vol. 124, pp. 54–73, 2016.
- [22] Y. G. Zhang, Y. Xu, and Z. P. Wang, “GM (1,1) Gray Prediction of Lorenz Chaotic System” Chaos Solitons and Fractals vol. 42, pp. 1003–1009, 2009.
- [23] Y. G. Zhang, J. Y. Yang, K. C. Wang, Z. P. Wang, and Y. D. Wang, “Lorenz Wind Disturbance Model Based on Grey Generated Components”, Energies vol. 7, pp. 7178–7193, 2014.
- [24] Y. G. Zhang, J. Y. Yang, K. C. Wang, Z. P. Wang, and Y. D. Wang, “Wind Power Prediction Considering Nonlinear Atmospheric Disturbance”, Energies vol. 8, pp. 475–478, 2014.
- [25] Y. G. Zhang, C. H. Zhang, Y. Zhao, and S. Gao, “Wind Speed Prediction with RBF Neural Network Based on PCA and ICA”, Journal of Electrical Engineering vol. 69, no. 2, pp. 148–155, 2018.