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Jun Zhan

National University of Defense Technology

Changsha Hunan, 410073

China

  • National University of Defense Technology

SCHOLARLY PAPERS

2

DOWNLOADS

90

TOTAL CITATIONS

2

Scholarly Papers (2)

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1.

Wind Turbine Short-Term Power Forecasting Method Based on Wind Speed Correction and Probabilistic Neural Network

Downloads 51 (1,086,013)
Citation 2

Wind Turbine Short-Term Power Forecasting Method Based on Wind Speed Correction and Probabilistic Neural Network

Number of pages: 18 Posted: 17 Apr 2024
jiewen deng, Zhao Xiao, Qiancheng Zhao, Jun Zhan, Jie Tao, Minghua Liu and Dongran Song
Hunan University of Science and Technology, Hunan University of Science and Technology, Hunan University of Science and Technology, National University of Defense Technology, Hunan University of Science and Technology, Hunan University of Science and Technology and Central South University
Downloads 27 (1,415,710)
Citation 2

Abstract:

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Probabilistic neural network, Wind speed correction, Short term power prediction, Wind Turbine

Wind Turbine Short-Term Power Forecasting Method Based on Wind Speed Correction and Probabilistic Neural Network

Number of pages: 18 Posted: 06 Mar 2024
Zhao Xiao, jiewen deng, Qiancheng Zhao, Jun Zhan, Jie Tao, Minghua Liu and Dongran Song
Hunan University of Science and Technology, Hunan University of Science and Technology, Hunan University of Science and Technology, National University of Defense Technology, Hunan University of Science and Technology, Hunan University of Science and Technology and Central South University
Downloads 24 (1,473,203)

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Probabilistic neural network, Wind speed correction, Short term power prediction；Wind turbine

2.

Hfn:Heterogeneous Feature Network for Multivariate Time Series Anomaly Detection

Number of pages: 34 Posted: 02 Feb 2023
Jun Zhan, Chengkun Wu, Canqun Yang, Qiucheng Miao and Xiandong Ma
National University of Defense Technology, National University of Defense Technology, affiliation not provided to SSRN, National University of Defense Technology and Lancaster University
Downloads 39 (1,222,651)

Abstract:

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Heterogeneous neural network, Anomaly detection, Multi-sensor data, Multivariate Time series, deep learning