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International Journal of Green Energy Volume 13, 2016 - Issue 6
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Original Articles

A hybrid model based on smooth transition periodic autoregressive and Elman artificial neural network for wind speed forecasting of the Hebei region in China

Shanshan QinSchool of Mathematics and Statistics, Lanzhou University, Lanzhou, China;Department of Mathematics and Statistics, York University, Toronto, Ontario, Canada
,
Jianzhou WangSchool of Statistics, Dongbei University of Finance and Economics, Dalian, ChinaCorrespondence[email protected]
,
Jie WuSchool of Mathematics and Statistics, Lanzhou University, Lanzhou, China
&
Ge ZhaoDepartment of Statistics, University of South Carolina, Columbia, South Carolina, USA
Pages 595-607 | Published online: 06 Jul 2016

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Huajian Yang, Wangqiang Niu, Xiaotong Wang & Wei Gu. (2023) Wind turbine output power forecasting based on temporal convolutional neural network and complete ensemble empirical mode decomposition with adaptive noise. International Journal of Green Energy 20:14, pages 1612-1627.
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Ufuk Yolcu, Erol Egrioglu, Eren Bas, Ozge Cagcag Yolcu & Ali Zafer Dalar. (2021) Probabilistic forecasting, linearity and nonlinearity hypothesis tests with bootstrapped linear and nonlinear artificial neural network. Journal of Experimental & Theoretical Artificial Intelligence 33:3, pages 383-404.
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Sunil Kumar Sharma & Sajal Ghosh. (2016) Short-term wind speed forecasting: Application of linear and non-linear time series models. International Journal of Green Energy 13:14, pages 1490-1500.
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Articles from other publishers (11)

Boqiang Lin & Chongchong Zhang. (2021) A novel hybrid machine learning model for short-term wind speed prediction in inner Mongolia, China. Renewable Energy 179, pages 1565-1577.
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M.C. Pegalajar, L.G.B. Ruiz, M.P. Cuéllar & R. Rueda. (2021) Analysis and enhanced prediction of the Spanish Electricity Network through Big Data and Machine Learning techniques. International Journal of Approximate Reasoning 133, pages 48-59.
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Jicheng Quan & Li Shang. (2021) An Ensemble Model of Wind Speed Forecasting Based on Variational Mode Decomposition and Bare-Bones Fireworks Algorithm. Mathematical Problems in Engineering 2021, pages 1-16.
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Hui Liu. 2021. Wind Forecasting in Railway Engineering. Wind Forecasting in Railway Engineering 1 44 .
K. U. Jaseena & Binsu C. Kovoor. (2020) A hybrid wind speed forecasting model using stacked autoencoder and LSTM. Journal of Renewable and Sustainable Energy 12:2, pages 023302.
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Mirza Naveed Shahzad, Saiqa Kanwal & Abid Hussanan. (2020) A New Hybrid ARAR and Neural Network Model for Multi-Step Ahead Wind Speed Forecasting in Three Regions of Pakistan. IEEE Access 8, pages 199382-199392.
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Cheng Peng, Zhaohui Tang, Qing Chen, Songsong Wang, Xiaohong Zhou & Hao Chi. (2019) Short-Term Prediction of Generator Blade Ice Fault Based on Multi-AN. Short-Term Prediction of Generator Blade Ice Fault Based on Multi-AN.
Yaguang Kong, Chenfeng Xie, Song Zheng, Peng Jiang, Meng Guan & Fang Wang. (2019) Dynamic Early Warning Method for Major Hazard Installation Systems in Chemical Industrial Park. Complexity 2019, pages 1-18.
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L.G.B. Ruiz, M.I. Capel & M.C. Pegalajar. (2019) Parallel memetic algorithm for training recurrent neural networks for the energy efficiency problem. Applied Soft Computing 76, pages 356-368.
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L.G.B. Ruiz, R. Rueda, M.P. Cuéllar & M.C. Pegalajar. (2018) Energy consumption forecasting based on Elman neural networks with evolutive optimization. Expert Systems with Applications 92, pages 380-389.
Crossref
Wei Sun & Yuwei Wang. (2018) Short-term wind speed forecasting based on fast ensemble empirical mode decomposition, phase space reconstruction, sample entropy and improved back-propagation neural network. Energy Conversion and Management 157, pages 1-12.
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