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Comparison of LSSVR, M5RT, NF-GP, and NF-SC Models for Predictions of Hourly Wind Speed and Wind Power Based on Cross-Validation

机译：LSSVR，M5RT，NF-GP和NF-SC模型的比较基于交叉验证的每小时风速和风能预测

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Rana Adnan; Zhongmin Liang; Xiaohui Yuan; Ozgur Kisi; Muhammad Akhlaq; Binquan Li;
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1. Comparison of LSSVR, M5RT, NF-GP, and NF-SC Models for Predictions of Hourly Wind Speed and Wind Power Based on Cross-Validation [J] . Rana Muhammad Adnan, Zhongmin Liang, Xiaohui Yuan, Energies . 2019,第2期

机译：基于交叉验证的小时风速和风电功率预测的LSSVR，M5RT，NF-GP和NF-SC模型的比较
2. Comparison Between Wind Power Prediction Models Based on Wavelet Decomposition with Least-Squares Support Vector Machine (LS-SVM) and Artificial Neural Network (ANN) [J] . Antonio Ficarella, Maria Grazia De Giorgi, Paolo Maria Congedo, Energies . 2014,第8期

机译：基于小波分解的最小二乘支持向量机（LS-SVM）和人工神经网络（ANN）的风电功率预测模型的比较
3. A robust stochastic stability analysis approach for power system considering wind speed prediction error based on Markov model [J] . Zigang Lu, Shufeng Lu, Minrui Xu, Computer standards & interfaces . 2021,第Apra期

机译：基于Markov模型的风速预测误差考虑风速预测误差的强大随机稳定性分析方法
4. Comparison of Different Wind Speed Prediction Models for Wind Power Application [C] . Temitope Raphael Ayodele, Richard Olarewaju, Josiah Lange Munda Southern African Universities Power Engineering Conference;Robotics and Mechatronics;Pattern Recognition Association of South Africa . 2019

机译：风电应用中不同风速预测模型的比较
5. Short-term forecasting of wind speed and wind power based on BP and Adaboost_BP. [D] . Mi, Sibei. 2014

机译：基于BP和Adaboost_BP的风速和风能的短期预测。
6. Twin Least Square Support Vector Regression Model Based on Gauss-Laplace Mixed Noise Feature with Its Application in Wind Speed Prediction [O] . Shiguang Zhang, Chao Liu, Wei Wang, 2020

机译：基于高斯拉普拉斯混合噪声功能的双重方形支持向量复频模型及其在风速预测中的应用
7. One‐day ahead wind speed/power prediction based on polynomial autoregressive model [O] . Oktay Karakuş, Ercan E. Kuruoğlu, Mustafa A. Altınkaya 2017

机译：基于多项式自回归模型的一天提前风速/功率预测

Comparison of LSSVR, M5RT, NF-GP, and NF-SC Models for Predictions of Hourly Wind Speed and Wind Power Based on Cross-Validation

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