scholarly journals Application of Cloud Model and Bayesian Network to Piracy Risk Assessment

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Kefeng Liu ◽  
Lizhi Yang ◽  
Ming Li
Keyword(s):  
Risk Assessment ◽  
Bayesian Network ◽  
Cloud Model ◽  
Indicator System ◽  
Assessment Model ◽  
Emergency Plan ◽  
Proposed Model ◽  
Set Up ◽  
Major Factors ◽  
Cloud Model Theory

Piracy is a major threat to maritime safety. Assessing piracy risk is crucial to ship safety, travel security, and emergency plan preparation. In the absence of a thorough understanding of the factors and mechanisms that influence piracy, no perfect mathematical equation can be set up for such risk assessment. Therefore, the major factors that influence piracy were identified to construct an indicator system for assessment. These factors were analyzed, keeping in view the overall hazard, vulnerability, and antirisk properties, and then the Bayesian network was introduced into the risk assessment model to fuse multiresource information. For some indicators, which have only qualitative information or fragmentary statistical data, the cloud model theory was adopted to realize prior probability settings of the Bayesian network and thus made up for the deficiency in parameter settings. Finally, the inherent hazard of the South China Sea was assessed, as an example for the model, and two real piracy cases were studied to validate the proposed model. The assessment model constructed here can be applied to all cases, similar to the ones studied here.

Supply Chain Risk Evaluation Based on Bayesian Network

2013 ◽  
Vol 680 ◽  
pp. 550-553
Author(s):  
Bo Chao Liu
Keyword(s):  
Risk Assessment ◽  
Supply Chain ◽  
Bayesian Network ◽  
Risk Evaluation ◽  
Evaluation Model ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Supply Chain Risk ◽  
Logistics Company ◽  
Proposed Model

The evaluation for supply chain risk is very important to show the latent risk and eliminate the risk. In the study, Bayesian network is proposed to evaluate the supply chain risk. The assessment indexes of supply chain risk are analyzed before supply chain risk assessment. Then, the assessment indexes of supply chain risk can be used to construct the supply chain risk assessment model. We apply a certain logistics company to study the evaluation ability of Bayesian network evaluation model proposed here. The experimental results prove the effectiveness of the proposed model.

scholarly journals Hesitant Cloud Model and Its Application in the Risk Assessment of “The Twenty-First Century Maritime Silk Road”

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Lizhi Yang ◽  
Ren Zhang ◽  
Taiping Hou ◽  
Zhinan Hao ◽  
Jun Liu
Keyword(s):  
Model Theory ◽  
Cloud Model ◽  
Indicator System ◽  
Silk Road ◽  
Hesitant Fuzzy Set ◽  
Human Environment ◽  
Maritime Silk Road ◽  
Qualitative Knowledge ◽  
Set Up ◽  
Cloud Model Theory

The evaluation of human environment risk is lacking quantitative data, while the qualitative knowledge cannot be easily quantified and synthesized. Furthermore, sometimes the experts are not well acknowledged with the whole indicator system or cannot reach an agreement on the comments. The conventional evaluation methods are not competent to solve the above aporia effectively. Thus the quantization of the human environment risk becomes a conundrum. The compatibility cloud model theory can set up a conversion model between the qualitative knowledge and quantitative value, which provides technique approaches to evaluating the risk of human environment. However, the hesitant opinion of experts stemming from the missing knowledge of the whole system or the branching opinions cannot be well solved by the traditional compatibility cloud model theory. Therefore, this paper brings in the theory of hesitant fuzzy set, combining with the cloud model theory, to try to construct a hesitant cloud model to achieve the quantitative assessment of human environment risk. And at last an experiment evaluation on the risk of maritime silk road is carried out.

scholarly journals A Case Study of Flood Risk Evaluation Based on Emergy Theory and Cloud Model in Anyang Region, China

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 420
Author(s):  
Zening Wu ◽  
Yuhai Cui ◽  
Yuan Guo
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Flood Control ◽  
Flood Hazard ◽  
Cloud Model ◽  
Flood Disaster ◽  
Assessment System ◽  
Assessment Model ◽  
Flood Risk Assessment ◽  
Emergy Theory

With the progression of climate change, the intensity and frequency of extreme rainfall have increased in many parts of the world, while the continuous acceleration of urbanization has made cities more vulnerable to floods. In order to effectively estimate and assess the risks brought by flood disasters, this paper proposes a regional flood disaster risk assessment model combining emergy theory and the cloud model. The emergy theory can measure many kinds of hazardous factor and convert them into unified solar emergy (sej) for quantification. The cloud model can transform the uncertainty in flood risk assessment into certainty in an appropriate way, making the urban flood risk assessment more accurate and effective. In this study, the flood risk assessment model combines the advantages of the two research methods to establish a natural and social dual flood risk assessment system. Based on this, the risk assessment system of the flood hazard cloud model is established. This model was used in a flood disaster risk assessment, and the risk level was divided into five levels: very low risk, low risk, medium risk, high risk, and very high risk. Flood hazard risk results were obtained by using the entropy weight method and fuzzy transformation method. As an example for the application of this model, this paper focuses on the Anyang region which has a typical continental monsoon climate. The results show that the Anyang region has a serious flood disaster threat. Within this region, Linzhou County and Anyang County have very high levels of risk for flood disaster, while Hua County, Neihuang County, Wenfeng District and Beiguan District have high levels of risk for flood disaster. These areas are the core urban areas and the economic center of local administrative regions, with 70% of the industrial clusters being situated in these regions. Only with the coordinated development of regional flood control planning, economy, and population, and reductions in the uncertainty of existing flood control and drainage facilities can the sustainable, healthy and stable development of the region be maintained.

scholarly journals PROPOSING A NEW METHODOLOGY BASED ON FUZZY LOGIC FOR TUNNELLING RISK ASSESSMENT

2014 ◽  
Vol 20 (1) ◽  
pp. 82-94 ◽  
Author(s):  
Abdolreza Yazdani-Chamzini
Keyword(s):  
Risk Assessment ◽  
Fuzzy Inference ◽  
Assessment Model ◽  
Tunnel Construction ◽  
Construction Operations ◽  
Protective Measures ◽  
Inference System ◽  
Proposed Model ◽  
Mine Development ◽  
Civil Defence

Tunnels are artificial underground spaces that provide a capacity for particular goals such as storage, under-ground transportation, mine development, power and water treatment plants, civil defence. This shows that the tunnel construction is a key activity in developing infrastructure projects. In many situations, tunnelling projects find themselves involved in the situations where unexpected conditions threaten the continuity of the project. Such situations can arise from the prior knowledge limited by the underground unknown conditions. Therefore, a risk analysis that can take into account the uncertainties associated with the underground projects is needed to assess the existing risks and prioritize them for further protective measures and decisions in order to reduce, mitigate and/or even eliminate the risks involved in the project. For this reason, this paper proposes a risk assessment model based on the concepts of fuzzy set theory to evaluate risk events during the tunnel construction operations. To show the effectiveness of the proposed model, the results of the model are compared with those of the conventional risk assessment. The results demonstrate that the fuzzy inference system has a great potential to accurately model such problems.

Optimized Based on Cloud Model Extension Assessment of Slope Stability

2010 ◽  
Vol 163-167 ◽  
pp. 2709-2714
Author(s):  
Feng Guo ◽  
Wei Ya Xu ◽  
Fei Xu
Keyword(s):  
Slope Stability ◽  
Cloud Model ◽  
Assessment Model ◽  
Actual State ◽  
Hydropower Project ◽  
Model Extension ◽  
Project Construction ◽  
The One ◽  
Cloud Model Theory

Evaluation of slope stability in the hydropower project construction is extremely important. This Cloud Model will be introduced to the matter-element extension, the extension assessment is proposed based on the sutra field division of the slope stability assessment model. This method combines the Cloud Model theory and the advantages of the extension assessment .On the one hand, the division of the sutra field by means of Cloud Model can overcome the "hard" division of the evils. On the other hand,with different values of Cloud Drops as a sutra field, the statistical results of Cloud Drops can be used as last stable assessment results. Project case study shows that compared with the conventional method, results of the method of extension are more accurate, which fully accorded with the actual state, proving optimized based on Cloud Model extension assessment of slope stability feasible and effective.

Establishment of Risk Assessment Model for Ship Collision using Applied Bayesian Network -Collision Accidents between Fishing vessels and Cargo Vessels -

2015 ◽  
Author(s):  
Takeshi Shinoda ◽  
Koji Uru
Keyword(s):  
Risk Assessment ◽  
Bayesian Network ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Benefit Analysis ◽  
Fishing Vessels ◽  
Formal Safety Assessment ◽  
Trial Cost

In this study, a risk assessment model for ship collisions is proposed according to the guidelines for Formal Safety Assessment (FSA) approved by IMO in 2002. The analysis is applied to ship collisions between fishing and cargo vessels owing to their high frequency and enormous damage. Bayesian network theory for risk analysis has been applied to reveal a causal relationship on human factors. A trial evaluation of Risk Control Options (RCOs) for collisions is attempted through the calculation of the dominance index. Finally, a trial cost benefit analysis for RCOs is considered through Gross Cost of Averting Fatality (GCAF) in FSA.

scholarly journals A Dynamic Risk Assessment Method for Deep-Buried Tunnels Based on a Bayesian Network

Geofluids ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
Yan Wang ◽  
Jie Su ◽  
Sulei Zhang ◽  
Siyao Guo ◽  
Peng Zhang ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Bayesian Network ◽  
Influencing Factors ◽  
Assessment Method ◽  
Assessment Model ◽  
Risk Level ◽  
Dynamic Risk ◽  
Risk Rating ◽  
Risk Assessment Method ◽  
Dynamic Risk Assessment

In view of the shortcomings in the risk assessment of deep-buried tunnels, a dynamic risk assessment method based on a Bayesian network is proposed. According to case statistics, a total of 12 specific risk rating factors are obtained and divided into three types: objective factors, subjective factors, and monitoring factors. The grading criteria of the risk rating factors are determined, and a dynamic risk rating system is established. A Bayesian network based on this system is constructed by expert knowledge and historical data. The nodes in the Bayesian network are in one-to-one correspondence with the three types of influencing factors, and the probability distribution is determined. Posterior probabilistic and sensitivity analyses are carried out, and the results show that the main influencing factors obtained by the two methods are basically the same. The constructed dynamic risk assessment model is most affected by the objective factor rating and monitoring factor rating, followed by the subjective factor rating. The dynamic risk rating is mainly affected by the surrounding rock level among the objective factors, construction management among the subjective factors, and arch crown convergence and side wall displacement among the monitoring factors. The dynamic risk assessment method based on the Bayesian network is applied to the No. 3 inclined shaft of the Humaling tunnel. According to the adjustment of the monitoring data and geological conditions, the dynamic risk rating probability of level I greatly decreased from 81.7% to 33.8%, the probability of level II significantly increased from 12.3% to 34.0%, and the probability of level III increased from 5.95% to 32.2%, which indicates that the risk level has risen sharply. The results show that this method can effectively predict the risk level during tunnel construction.

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