Clustering-Based Hybrid Approach for Wind Speed Forecasting

2022 ◽  
pp. 587-598
Author(s):  
Vendra Akhil ◽  
Rajesh Wadhvani ◽  
Manasi Gyanchandani ◽  
Anil Kumar Kushwah
Keyword(s):  
Wind Speed ◽  
Hybrid Approach ◽  
Wind Speed Forecasting

A hybrid approach for multi-step wind speed forecasting based on two-layer decomposition, improved hybrid DE-HHO optimization and KELM

2021 ◽  
Vol 164 ◽  
pp. 211-229 ◽  
Author(s):  
Wenlong Fu ◽  
Kai Zhang ◽  
Kai Wang ◽  
Bin Wen ◽  
Ping Fang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Hybrid Approach ◽  
Wind Speed Forecasting

scholarly journals A Hybrid Wavelet Transform Based Short-Term Wind Speed Forecasting Approach

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Jujie Wang
Keyword(s):  
Wavelet Transform ◽  
Wind Speed ◽  
Network Architecture ◽  
Hybrid Approach ◽  
Experimental Simulation ◽  
Wind Speed Forecasting ◽  
Optimal Network ◽  
Partial Autocorrelation Function ◽  
Parks Management ◽  
Hidden Layer

It is important to improve the accuracy of wind speed forecasting for wind parks management and wind power utilization. In this paper, a novel hybrid approach known as WTT-TNN is proposed for wind speed forecasting. In the first step of the approach, a wavelet transform technique (WTT) is used to decompose wind speed into an approximate scale and several detailed scales. In the second step, a two-hidden-layer neural network (TNN) is used to predict both approximated scale and detailed scales, respectively. In order to find the optimal network architecture, the partial autocorrelation function is adopted to determine the number of neurons in the input layer, and an experimental simulation is made to determine the number of neurons within each hidden layer in the modeling process of TNN. Afterwards, the final prediction value can be obtained by the sum of these prediction results. In this study, a WTT is employed to extract these different patterns of the wind speed and make it easier for forecasting. To evaluate the performance of the proposed approach, it is applied to forecast Hexi Corridor of China’s wind speed. Simulation results in four different cases show that the proposed method increases wind speed forecasting accuracy.

A self-adaptive hybrid approach for wind speed forecasting

2015 ◽  
Vol 78 ◽  
pp. 374-385 ◽  
Author(s):  
Jianzhou Wang ◽  
Jianming Hu ◽  
Kailiang Ma ◽  
Yixin Zhang
Keyword(s):  
Wind Speed ◽  
Hybrid Approach ◽  
Wind Speed Forecasting ◽  
Self Adaptive

scholarly journals Hybrid Approach Combining SARIMA and Neural Networks for Multi-Step Ahead Wind Speed Forecasting in Brazil

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 55986-55994 ◽  
Author(s):  
David B. Alencar ◽  
Carolina M. Affonso ◽  
Roberto C. L. Oliveira ◽  
Jose C. R. Filho
Keyword(s):  
Neural Networks ◽  
Wind Speed ◽  
Hybrid Approach ◽  
Wind Speed Forecasting

scholarly journals Meta Learning-Based Hybrid Ensemble Approach for Short-Term Wind Speed Forecasting

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 172859-172868
Author(s):  
Zhengwei Ma ◽  
Sensen Guo ◽  
Gang Xu ◽  
Saddam Aziz
Keyword(s):  
Wind Speed ◽  
Short Term ◽  
Wind Speed Forecasting ◽  
Ensemble Approach ◽  
Meta Learning
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