@inproceedings{6c63d74d7b344a009d4ca0aba5b41463,
title = "A Novel Approach to Ship Operational Risk Analysis Based on D-S Evidence Theory",
abstract = "In view of the complex environment in which risk analysis of ship accidents is carried out, and the uncertainty and ambiguity of experts{\textquoteright} judgements in risk analysis, this paper proposes a risk analysis method based on intuitionistic fuzzy linguistic set and D-S evidence theory. Intuitionistic fuzzy entropy is applied to determine the weight of each criterion, and then the risk value of m for each attribute is aggregated based on D-S evidence theory. In terms of expert information aggregation, expert weights are firstly obtained based on evidence distance and fuzzy entropy, and then experts{\textquoteright} judgements for attributes are merged via D-S theory to yield the risk ranking of each attribute. Finally, a cruise ship collision scenario is provided as a case to verify the rationality and effectiveness of the proposed method. The result validates that D-S evidence theory is an efficient tool for ship risk analysis.",
author = "Tao Liu and Yuanzi Zhou and Junzhong Bao and Xizhao Wang and Pengfei Zhang",
year = "2021",
month = aug,
day = "20",
doi = "10.1007/978-981-16-5188-5_52",
language = "English",
isbn = "978-981-16-5187-8",
series = "Communications in Computer and Information Science",
publisher = "Springer Singapore",
pages = "728--741",
editor = "H. Zhang and Z. Yang and Z. Zhang and Z. Wu and T. Hao",
booktitle = "Neural Computing for Advanced Applications",
address = "Singapore",
note = "Neural Computing for Advanced Applications : Second International Conference, NCAA 2021 ; Conference date: 27-08-2021 Through 30-08-2021",
}