Items where Salford Author is "An, Professor Min"

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Number of items: 9.

Article

Dindar, S, Kaewunruen, S, An, M ORCID: 0000-0002-1069-7492 and Sussman, JM 2018, 'Bayesian network-based probability analysis of train derailments caused by various extreme weather patterns on railway turnouts' , Safety Science, 110 (Part B) , pp. 20-30.
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Wang, L, An, M ORCID: 0000-0002-1069-7492, Qin, Y and Jia, L 2018, 'A risk-based maintenance decision-making approach for railway asset management' , International Journal of Software Engineering and Knowledge Engineering (ijseke), 28 (4) , pp. 453-483.
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Qin, Y, An, M ORCID: 0000-0002-1069-7492 and Jia, LM 2018, 'Guest editors' introduction' , International Journal of Software Engineering and Knowledge Engineering (ijseke), 28 (04) , pp. 427-429.
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Dindar, S, Kaewunruen, S and An, M ORCID: 0000-0002-1069-7492 2018, 'Identification of appropriate risk analysis techniques for railway turnout systems' , Journal of Risk Research, 21 (8) , pp. 974-995.
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Dindar, S, Kaewunruen, S, An, M ORCID: 0000-0002-1069-7492 and Gigante-Barrera, A 2017, 'Derailment-based fault tree analysis on risk management of railway turnout systems' , IOP Conference Series: Materials Science and Engineering, 245 (II) , 042020.
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Dindar, S, Kaewunruen, S, An, M ORCID: 0000-0002-1069-7492 and Osman, M 2016, 'Natural hazard risks on railway turnout systems' , Procedia Engineering, 161 , pp. 1254-1259.
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An, M ORCID: 0000-0002-1069-7492, Qin, Y, Jia, L and Chen, Y 2016, 'Aggregation of group fuzzy risk information in the railway risk decision making process' , Safety Science, 82 , pp. 18-28.
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Conference or Workshop Item

Zhang, Y, An, M ORCID: 0000-0002-1069-7492, Wang, L and Lei, D 2017, Considerations of out-of-gauge freight transportation in railway infrastructure development and maintenance projects , in: International Research Conference 2017: Shaping Tomorrow's Built Environment, 11-12 September 2017, University of Salford, UK.
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Wang, Li, An, M ORCID: 0000-0002-1069-7492, Zhang, Y and Rana, K 2017, Railway network reliability analysis based on key station identification using complex network theory : a real-world case study of high-speed rail network , in: International Research Conference 2017 : Shaping Tomorrow's Built Environment, 11-12 October 2017, University of Salford, UK.
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This list was generated on Sat Dec 15 12:34:21 2018 UTC.