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Yonghong Liu

affiliation not provided to SSRN

  • affiliation not provided to SSRN

SCHOLARLY PAPERS

3

DOWNLOADS

170

TOTAL CITATIONS

2

Scholarly Papers (3)

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1.

A Novel Dynamic Bayesian Network-Based Dynamic Fault Diagnosis Method Integrating Original Monitoring Information

Number of pages: 26 Posted: 17 Feb 2022
Baoping Cai, Zhengde Chu, Chao Yang, Xiangdi Kong, Zhengda Wang, Longting Wang, Yonghong Liu and Guijie Liu
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN and Ocean University of China
Downloads 71 (867,774)

Abstract:

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Subsea Christmas tree, Dynamic diagnosis, Dynamic Bayesian network, Original information

2.

Dynamic Optimization Method of Subsea Production Scheme Based on Mixed Mutation Flower Pollination Algorithm

Number of pages: 20 Posted: 05 Apr 2023
Gongbo Li, Honghui Wang, Guijie Liu, Yonghong Liu, Baoping Cai, Bo Hu, Xin Fang and Guanghao Li
Ocean University of China, Ocean University of China, Ocean University of China, affiliation not provided to SSRN, affiliation not provided to SSRN, Ocean University of China, Ocean University of China and Ocean University of China
Downloads 52 (1,041,696)

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subsea production system, multi-objective optimization, mutation flower pollination algorithm

3.

A Dynamic and Quantitative Risk Assessment Method for Marine Oil Spills Accruing in Extreme Winds Based on Dynamic Bayesian Network

Number of pages: 1 Posted: 09 Jul 2022
Zengkai Liu, Zhonghao Han, Qi Chen, Xuewei Shi, Qiang Ma, Baoping Cai and Yonghong Liu
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN and affiliation not provided to SSRN
Downloads 47 (1,097,529)
Citation 2

Abstract:

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Oil spill, Quantitative risk assessment, Dynamic Bayesian network, Annual extreme wind