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An EMD Based Polynomial Kernel Methodology for superior Wind Power Prediction.
2019 1st International Conference on Artificial Intelligence and Data Sciences (AiDAS)
◽
10.1109/aidas47888.2019.8970690
◽
2019
◽
Author(s):
S. P. Mishra
◽
R.K. Patnaik
◽
P. K. Dash
◽
R. Bisoi
◽
J. Naik
Keyword(s):
Wind Power
◽
Polynomial Kernel
◽
Power Prediction
◽
Wind Power Prediction
Download Full-text
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Cited By
References
Short-Term Wind Power Prediction for Wind Turbine via Kalman Filter based on JIT Modeling
IEEJ Transactions on Electronics Information and Systems
◽
10.1541/ieejeiss.135.81
◽
2015
◽
Vol 135
(1)
◽
pp. 81-89
◽
Cited By ~ 2
Author(s):
Tomoki Ishikawa
◽
Takaaki Kojima
◽
Toru Namerikawa
Keyword(s):
Kalman Filter
◽
Wind Turbine
◽
Wind Power
◽
Power Prediction
◽
Short Term
◽
Wind Power Prediction
Download Full-text
Research on wind power prediction based on Doppler Sodar
2020 Chinese Automation Congress (CAC)
◽
10.1109/cac51589.2020.9326699
◽
2020
◽
Author(s):
Gao Yang
◽
Shu Xinlei
◽
Liu Baoliang
◽
Sun Wenzhong
◽
Zhao Mingjiang
◽
...
Keyword(s):
Wind Power
◽
Power Prediction
◽
Wind Power Prediction
◽
Doppler Sodar
Download Full-text
A Short-Term Regional Wind Power Prediction Method Based on XGBoost and Multi-stage Features Selection
2020 IEEE 3rd Student Conference on Electrical Machines and Systems (SCEMS)
◽
10.1109/scems48876.2020.9352249
◽
2020
◽
Author(s):
Wenze Li
◽
Xiaosheng Peng
◽
Kai Cheng
◽
Hongyu Wang
◽
Qiyou Xu
◽
...
Keyword(s):
Wind Power
◽
Prediction Method
◽
Features Selection
◽
Power Prediction
◽
Short Term
◽
Multi Stage
◽
Wind Power Prediction
Download Full-text
EALSTM-QR: Interval wind-power prediction model based on numerical weather prediction and deep learning
Energy
◽
10.1016/j.energy.2020.119692
◽
2020
◽
pp. 119692
Author(s):
Xiaosheng Peng
◽
Hongyu Wang
◽
Jianxun Lang
◽
Wenze Li
◽
Qiyou Xu
◽
...
Keyword(s):
Deep Learning
◽
Prediction Model
◽
Wind Power
◽
Numerical Weather Prediction
◽
Weather Prediction
◽
Power Prediction
◽
Numerical Weather
◽
Model Based
◽
Wind Power Prediction
Download Full-text
A hybrid model for wind power prediction composed of ANN and imperialist competitive algorithm (ICA)
2014 22nd Iranian Conference on Electrical Engineering (ICEE)
◽
10.1109/iraniancee.2014.6999606
◽
2014
◽
Cited By ~ 1
Author(s):
Amin Shokri Gazafroudi
◽
Nooshin Bigdeli
◽
Mostafa Yousefi Ramandi
◽
Karim Afshar
Keyword(s):
Wind Power
◽
Hybrid Model
◽
Imperialist Competitive Algorithm
◽
Power Prediction
◽
Competitive Algorithm
◽
Wind Power Prediction
Download Full-text
Short-Term Wind Power Prediction Based on Principal Component Analysis and Elman Artificial Neural Networks
2017 4th International Conference on Information Science and Control Engineering (ICISCE)
◽
10.1109/icisce.2017.146
◽
2017
◽
Cited By ~ 1
Author(s):
Shaung Hu
◽
Ke-Jun Li
Keyword(s):
Neural Networks
◽
Principal Component Analysis
◽
Artificial Neural Networks
◽
Wind Power
◽
Principal Component
◽
Component Analysis
◽
Power Prediction
◽
Short Term
◽
Wind Power Prediction
◽
Artificial Neural
Download Full-text
Short-Term Wind Power Prediction Considering the Influence of Terrain
International Journal of Simulation Systems Science & Technology
◽
10.5013/ijssst.a.17.38.28
◽
2016
◽
Author(s):
Guest Editor Manhui Su
Keyword(s):
Wind Power
◽
Power Prediction
◽
Short Term
◽
Wind Power Prediction
Download Full-text
A Multivariate Wind Power Prediction Model Based on Wavelet Transformation Noise Reduction
Proceedings of the 2018 International Conference on Machine Learning Technologies - ICMLT '18
◽
10.1145/3231884.3231891
◽
2018
◽
Author(s):
Xinyue Ji
◽
Mengyao Hu
◽
Xiaoyu Zhang
Keyword(s):
Prediction Model
◽
Noise Reduction
◽
Wind Power
◽
Wavelet Transformation
◽
Power Prediction
◽
Model Based
◽
Wind Power Prediction
Download Full-text
Wind power prediction with missing data using Gaussian process regression and multiple imputation
Applied Soft Computing
◽
10.1016/j.asoc.2018.07.027
◽
2018
◽
Vol 71
◽
pp. 905-916
◽
Cited By ~ 24
Author(s):
Tianhong Liu
◽
Haikun Wei
◽
Kanjian Zhang
Keyword(s):
Missing Data
◽
Gaussian Process
◽
Multiple Imputation
◽
Wind Power
◽
Gaussian Process Regression
◽
Power Prediction
◽
Wind Power Prediction
Download Full-text
A dynamic adaptive algorithm for statistical up-scaling based short-term wind power prediction of regions
2017 China International Electrical and Energy Conference (CIEEC)
◽
10.1109/cieec.2017.8388524
◽
2017
◽
Author(s):
Xiaosheng Peng
◽
Yuzhu Chen
◽
Jianfeng Che
◽
Bo Wang
Keyword(s):
Wind Power
◽
Adaptive Algorithm
◽
Power Prediction
◽
Short Term
◽
Wind Power Prediction
◽
Up Scaling
Download Full-text
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