FedBIP: A Federated Learning-Based Model for Wind Turbine Blade Icing Prediction-Reference-Cited by-同舟云学术

FedBIP: A Federated Learning-Based Model for Wind Turbine Blade Icing Prediction

Author:

Zhang Dongtian¹^ORCID,Tian Weiwei²^ORCID,Cheng Xu¹^ORCID,Shi Fan¹^ORCID,Qiu Hong³^ORCID,Liu Xiufeng⁴^ORCID,Chen Shengyong¹^ORCID

Affiliation:

1. School of Computer Science and Engineering, Tianjin University of Technology, Tianjin, China

2. Department of Ocean Operations and Civil Engineering, Norwegian University of Science and Technology, Ålesund, Norway

3. College of Big Data and Software Engineering, Zhejiang Wanli University, Ningbo, China

4. Department of Technology, Management and Economics, Technical University of Denmark, Kongens Lyngby, Denmark

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

Reference39 articles.

1. Communication-efficient learning of deep networks from decentralized data;mcmahan;Proc 20th Int Conf Artif Intell Statist,0

2. FedBN: Federated learning on non-IID features via local batch normalization;li;arXiv 2102 07623,2021

5. Waveletfcnn: A deep time series classification model for wind turbine blade icing detection;yuan;arXiv 1902 05625,2019

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