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25 April 2022 Multi-mode integrated method based on CART and its application in wind speed prediction
Gang Luo, Xiaofeng Yang, Xiang Zheng, Yuan Huang, Qiang Fan, Xinyi Ying, Bing Wang
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Proceedings Volume 12244, 2nd International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2022); 1224453 (2022) https://doi.org/10.1117/12.2635165
Event: 2nd International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2022), 2022, Guilin, China
Abstract
In recent years, weather forecast plays an extremely important role in new energy power generation as well as prediction and early warning of major meteorological disasters. To improve the accuracy and stability of forecast, it gradually changes from a single deterministic forecast to a multi-mode integrated forecast, that is, the combination of several independent forecast results. CART algorithm divides the global data set into multiple data sets that are easy to model and establishes a local regression model on each local data set, which is especially suitable for modeling complex data with multiple characteristic variables. Therefore, this paper mainly studies the multi-mode integrated method based on CART and its application in the forecast of wind speed. The wind speed sampling data of the European Center for Medium-Range Weather Forecasts and National Centers for Environmental Prediction are integrated by using the integrated method based on CART and compared with single-mode forecast and BREM. The results of the simulation show that the CART has a significant improvement in the accuracy of forecast compared with BREM and the traditional single-mode forecast.
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Gang Luo, Xiaofeng Yang, Xiang Zheng, Yuan Huang, Qiang Fan, Xinyi Ying, and Bing Wang "Multi-mode integrated method based on CART and its application in wind speed prediction", Proc. SPIE 12244, 2nd International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2022), 1224453 (25 April 2022); https://doi.org/10.1117/12.2635165
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KEYWORDS
Data modeling
Wind energy
Statistical modeling
Meteorology
Data centers
Process modeling
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