Hybrid Model Based on Isolated Forest and WT-Catboost for Wind Power Forecasting-Reference-Cited by-同舟云学术

Hybrid Model Based on Isolated Forest and WT-Catboost for Wind Power Forecasting

Published:2022-11-04 Issue: Volume: Page:
ISSN:
Container-title:2022 2nd International Conference on Computation, Communication and Engineering (ICCCE)
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Author:

Zhang Rongquan¹,Gao Jinfeng²,Zheng Yuxia¹,Xiong Jie¹,Wang Li³,Liu Fang²,Li Gangqiang²

Affiliation:

1. College of transportation, NanChang JiaoTong Institute,NanChang,China

2. College of Computer and Artificial Intelligence, Huanghuai University,Henan International Joint Laboratory of Behavior Optimization Control for Smart Robots & Henan Provincial Key Laboratory of Smart Lighting,Zhumadian,China

3. College of Mathematics and Statistics, Huanghuai University,Zhumadian,China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Henan Province

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10036126/10036192/10036227.pdf?arnumber=10036227

Reference12 articles.

1. Hybrid forecasting method for wind power integrating spatial correlation and corrected numerical weather prediction

2. Integrated Carbon-Capture-Based Low-Carbon Economic Dispatch of Power Systems Based on EEMD-LSTM-SVR Wind Power Forecasting

3. CatBoost: unbiased boosting with categorical features;prokhorenkova;Advances in neural information processing systems,2018

4. Short-term offshore wind power forecasting - A hybrid model based on Discrete Wavelet Transform (DWT), Seasonal Autoregressive Integrated Moving Average (SARIMA), and deep-learning-based Long Short-Term Memory (LSTM)

5. Data-driven cooperative trading framework for a risk-constrained wind integrated power system considering market uncertainties