A new dynamic integrated approach for wind speed forecasting
暂无分享,去创建一个
Shaolong Sun | Han Qiao | Shouyang Wang | Yunjie Wei | Shouyang Wang | H. Qiao | Shaolong Sun | Yunjie Wei
[1] Mingxi Wang,et al. Optimal investment and uncertainty on China's carbon emission abatement , 2012 .
[2] Tom Howard,et al. Correction and downscaling of NWP wind speed forecasts , 2007 .
[3] Ivor W. Tsang,et al. Core Vector Regression for very large regression problems , 2005, ICML.
[4] Bernhard Schölkopf,et al. Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.
[5] Jianzhou Wang,et al. A hybrid technique for short-term wind speed prediction , 2015 .
[6] Ainuddin Wahid Abdul Wahab,et al. An appraisal of wind speed distribution prediction by soft computing methodologies: A comparative study , 2014 .
[7] Hossein Nezamabadi-pour,et al. GSA: A Gravitational Search Algorithm , 2009, Inf. Sci..
[8] Sancho Salcedo-Sanz,et al. Feature selection in wind speed prediction systems based on a hybrid coral reefs optimization – Extreme learning machine approach , 2014 .
[9] Jie Wu,et al. Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its Application , 2015 .
[10] J. Salas,et al. Nonlinear dynamics, delay times, and embedding windows , 1999 .
[11] R. Barthelmie,et al. The economic benefit of short-term forecasting for wind energy in the UK electricity market , 2008 .
[12] Zijun Zhang,et al. Short-term wind speed forecasting with Markov-switching model , 2014 .
[13] Wang Jilong,et al. Short-term wind speed forecasting based on spectral clustering and optimised echo state networks , 2015 .
[14] Ivor W. Tsang,et al. Core Vector Machines: Fast SVM Training on Very Large Data Sets , 2005, J. Mach. Learn. Res..
[15] Osamah Basheer Shukur,et al. Daily wind speed forecasting through hybrid KF-ANN model based on ARIMA , 2015 .
[16] Zheng Yao,et al. Wind power forecasting based on principle component phase space reconstruction , 2015 .
[17] Jian Chai,et al. Why does energy intensity fluctuate in China , 2009 .
[18] Jie Tang,et al. Some improvements of wind speed Markov chain modeling , 2015 .
[19] Hui Liu,et al. Four wind speed multi-step forecasting models using extreme learning machines and signal decomposing algorithms , 2015 .
[20] Jianzhou Wang,et al. Medium-term wind speeds forecasting utilizing hybrid models for three different sites in Xinjiang, China , 2015 .
[21] Jianzhou Wang,et al. A hybrid forecasting model based on outlier detection and fuzzy time series – A case study on Hainan wind farm of China , 2014 .
[22] Jianzhou Wang,et al. The study and application of a novel hybrid forecasting model – A case study of wind speed forecasting in China , 2015 .
[23] Ching-Chih Chang. A multivariate causality test of carbon dioxide emissions, energy consumption and economic growth in China , 2010 .
[24] Ling Tang,et al. A novel seasonal decomposition based least squares support vector regression ensemble learning appro , 2011 .
[25] Jianping Li,et al. A novel hybrid ensemble learning paradigm for nuclear energy consumption forecasting , 2012 .
[26] Sina Mohseni,et al. Competition over Resources: A New Optimization Algorithm Based on Animals Behavioral Ecology , 2014, 2014 International Conference on Intelligent Networking and Collaborative Systems.
[27] Dayong Zhang,et al. Exuberance in China's renewable energy investment: Rationality, capital structure and implications with firm level evidence , 2016 .
[28] Jianzhou Wang,et al. Application of residual modification approach in seasonal ARIMA for electricity demand forecasting: A case study of China , 2012 .
[29] Wei-Chiang Hong,et al. Application of chaotic ant swarm optimization in electric load forecasting , 2010 .
[30] Hui Liu,et al. New wind speed forecasting approaches using fast ensemble empirical model decomposition, genetic algorithm, Mind Evolutionary Algorithm and Artificial Neural Networks , 2015 .
[31] Ping-Feng Pai,et al. Support Vector Machines with Simulated Annealing Algorithms in Electricity Load Forecasting , 2005 .
[32] A. A. Alazba,et al. Predictive model for assessing and optimizing solar still performance using artificial neural network under hyper arid environment , 2015 .
[33] Kin Keung Lai,et al. CRUDE OIL PRICE FORECASTING WITH TEI@I METHODOLOGY ∗ , 2005 .
[34] Ling Tang,et al. A novel data-characteristic-driven modeling methodology for nuclear energy consumption forecasting , 2014 .
[35] Yao Dong,et al. Coal production forecast and low carbon policies in China , 2011 .