Risk Cloud Model for Evaluating Nautical Navigational Environments
Uncertainty makes the risk evaluation of complex water transportation systems (WTSs) a difficult task. To achieve reasonable results while accounting for uncertainty, the risk evaluation of nautical navigational environments (NNEts) is often based on classical cloud model theory. This study proposes...
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Hindawi Limited
2021-01-01
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2021/8888865 |
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doaj-f671992484cf44819bc80b91afa6bd582021-04-12T01:24:09ZengHindawi LimitedMathematical Problems in Engineering1563-51472021-01-01202110.1155/2021/8888865Risk Cloud Model for Evaluating Nautical Navigational EnvironmentsLijia Chen0Yanfei Tian1School of NavigationSchool of Naval Architecture and MaritimeUncertainty makes the risk evaluation of complex water transportation systems (WTSs) a difficult task. To achieve reasonable results while accounting for uncertainty, the risk evaluation of nautical navigational environments (NNEts) is often based on classical cloud model theory. This study proposes the concept of a risk cloud model (RCM) for NNEt evaluation and uses a fuzzy statistics-based computational approach to obtain the RCM parameters. As a case study, the proposed RCM method was applied to the risk evaluation of the Qiongzhou Strait. The performance of the proposed method was compared to those of a fuzzy theory-based method and an earlier proposed simplified algorithm. The results of the case study demonstrated the effectiveness of the proposed method along with several key advantages. First, the method could deal with uncertainty, take advantage of multichannel information, and evaluate risk features. Second, the RCM droplets intuitively displayed the qualitative and quantitative characteristics of risk levels, which facilitated understanding and analysis. Third, it showed a good sensitivity to ensure the refinement of evaluation results. The proposed method offered an improved approach to NNEt risk evaluation under uncertain conditions.http://dx.doi.org/10.1155/2021/8888865 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lijia Chen Yanfei Tian |
spellingShingle |
Lijia Chen Yanfei Tian Risk Cloud Model for Evaluating Nautical Navigational Environments Mathematical Problems in Engineering |
author_facet |
Lijia Chen Yanfei Tian |
author_sort |
Lijia Chen |
title |
Risk Cloud Model for Evaluating Nautical Navigational Environments |
title_short |
Risk Cloud Model for Evaluating Nautical Navigational Environments |
title_full |
Risk Cloud Model for Evaluating Nautical Navigational Environments |
title_fullStr |
Risk Cloud Model for Evaluating Nautical Navigational Environments |
title_full_unstemmed |
Risk Cloud Model for Evaluating Nautical Navigational Environments |
title_sort |
risk cloud model for evaluating nautical navigational environments |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1563-5147 |
publishDate |
2021-01-01 |
description |
Uncertainty makes the risk evaluation of complex water transportation systems (WTSs) a difficult task. To achieve reasonable results while accounting for uncertainty, the risk evaluation of nautical navigational environments (NNEts) is often based on classical cloud model theory. This study proposes the concept of a risk cloud model (RCM) for NNEt evaluation and uses a fuzzy statistics-based computational approach to obtain the RCM parameters. As a case study, the proposed RCM method was applied to the risk evaluation of the Qiongzhou Strait. The performance of the proposed method was compared to those of a fuzzy theory-based method and an earlier proposed simplified algorithm. The results of the case study demonstrated the effectiveness of the proposed method along with several key advantages. First, the method could deal with uncertainty, take advantage of multichannel information, and evaluate risk features. Second, the RCM droplets intuitively displayed the qualitative and quantitative characteristics of risk levels, which facilitated understanding and analysis. Third, it showed a good sensitivity to ensure the refinement of evaluation results. The proposed method offered an improved approach to NNEt risk evaluation under uncertain conditions. |
url |
http://dx.doi.org/10.1155/2021/8888865 |
work_keys_str_mv |
AT lijiachen riskcloudmodelforevaluatingnauticalnavigationalenvironments AT yanfeitian riskcloudmodelforevaluatingnauticalnavigationalenvironments |
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1714683043920216064 |