Wind Power Prediction Based on Nonlinear AutoRegressive with eXogenous Inputs Algorithm-Reference-Cited by-同舟云学术

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Wind Power Prediction Based on Nonlinear AutoRegressive with eXogenous Inputs Algorithm

Published:2024-05-17 Issue: Volume: Page:345-350
ISSN:
Container-title:2024 IEEE 13th Data Driven Control and Learning Systems Conference (DDCLS)
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Author:

Wang Zhe¹,Zhang Heng¹,Fu Lingkun²,Li Ming¹,Zhang Jian¹,Li Hongran¹,Wang Jianbo³

Affiliation:

1. School of Computer Engineering, Jiangsu Ocean University,Lianyungang,P. R. China,222000

2. Zhejiang Yunda Wind Power Co,Hangzhou,P. R. China,310012

3. School of Marine Technology and Geomatics, Jiangsu Ocean University,Lianyungang,P. R. China,222000

Funder

National Natural Science Foundation (NSFC) of China

Natural Science Foundation of the Jiangsu Higher Education Institutions of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10606543/10606546/10606618.pdf?arnumber=10606618

Reference20 articles.

1. Can deep learning beat numerical weather prediction?

2. Distributed Load Sharing of an Inverter-Based Microgrid With Reduced Communication

3. Event-triggered finite-time resilient control for switched systems: an observer-based approach and its applications to a boost converter circuit system model

4. Deep Learning-Based Weather Prediction: A Survey

5. Machine learning based algorithms for uncertainty quantification in numerical weather prediction models

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