scholarly journals Based on Fuzzy Bayesian Network of Oil Wharf Handling Risk Assessment

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Zhiqiang Hou ◽  
Peng Zhao
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Bayesian Network ◽  
Evaluation Model ◽  
Calibration Method ◽  
Analytic Network Process ◽  
Assessment Method ◽  
Practical Significance ◽  
Tree Model ◽  
Safety Level

In order to make the risk assessment method of oil wharf handling more reasonable, basic data calibration method more accurate, and assessment findings more objective, the fuzzy weights of the relative probability of basic events are calibrated by ANP decision-making (Analytic Network Process). ANP decision-making is appropriate for reflecting the dependence between the basic events and the feedback relationship. The calibration value is used as the probability value of each basic event. Based on the fault tree model, the relationship between the accidents caused by the Bayesian network is constructed, and the important degree of the basic events is quantitatively evaluated. The case focuses on wharf handling gasoline fire and explosions, using ANP method to calibrate probability, and analyzing and sorting the structural importance, the probability importance, and critical degree of each basic event through forward and backward reasoning. The results showed that the evaluation model can better characterize the effect of the basic events on the top events, which can be targeted to identify security weaknesses in oil wharf handling process. It has some practical significance for finding security risks and improving working conditions and the overall system safety level.

scholarly journals Risk Assessment in PPP Projects by Applying Different MCDM Methods and Comparative Results Analysis

2018 ◽  
Vol 8 (4) ◽  
pp. 80 ◽  
Author(s):  
Alireza Valipour ◽  
Hadi Sarvari ◽  
Jolanta Tamošaitiene
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Construction Projects ◽  
Analytic Network Process ◽  
Assessment Method ◽  
Analytic Hierarchy ◽  
Risk Assessment Method ◽  
Network Process ◽  
Comparative Results ◽  
Simple Additive Weighting

Recently, risk assessment has become one of the most challenging issues in the areas of construction and public-private partnerships (PPPs). To address risk assessment issues, various decision-making techniques have been proposed, each with its own specific disadvantages and advantages. This paper investigates step-wise weight assessment ratio analysis (SWARA), complex proportional assessment (COPRAS), fuzzy analytic network process (FANP), fuzzy analytic hierarchy process (FAHP), fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS), simple additive weighting (SAW) and evaluation based on distance from average solution (EDAS) in order to define how various multi-attribute decision-making (MADM) methods compare when used for risk assessment in PPP projects. For this study, 5 risk assessment criteria and 10 types of risk used in Iranian highway PPP projects were selected. Four suitability and applicability tests were used to measure agreement between the rankings derived from the MADM methods. Final results show that all techniques had approximately the same rankings of risk assessment, with the SWARA, COPRAS, and EDAS methods performing slightly better. The findings of this study will help the parties in PPP and construction projects to select the best risk assessment method.

Bayesian mutual information reliability model for fire risk assessment of high-rise buildings

2020 ◽  
pp. 002072091989419
Author(s):  
Jingjing Pei ◽  
Guantao Wang
Keyword(s):  
Risk Assessment ◽  
Bayesian Network ◽  
Quantitative Assessment ◽  
Fire Risk ◽  
Event Tree ◽  
Bayesian Network Model ◽  
Tree Model ◽  
High Rise ◽  
Fire Risk Assessment ◽  
Information Reliability

The Bayesian network method is introduced into the process of fire risk quantitative assessment. The event tree model is established, and the Bayesian network model is transformed from the event tree model based on the typical fire scenarios in high-rise space. A Bayesian fire risk assessment algorithm for high-rise buildings based on mutual information reliability is proposed. Bayesian network is modified considering the influence of uncertainties. Finally, the modified Bayesian network model is used to calculate the probability of fire developing to different stages, and the estimated value of property loss is used to express the severity of the accident and calculate the fire risk value. The results show that the existence of uncertainties has a significant impact on the results of risk assessment; the quantitative assessment method based on Bayesian network is better than the ETA method based on event tree analysis in dealing with uncertainties and is more suitable for high-rise space fire risk assessment.

A hierarchical tree-based decision-making approach for assessing the relative trustworthiness of risk assessment models

2020 ◽  
Vol 234 (6) ◽  
pp. 748-763
Author(s):  
Tasneem Bani-Mustafa ◽  
Nicola Pedroni ◽  
Enrico Zio ◽  
Dominique Vasseur ◽  
Francois Beaudouin
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Nuclear Power ◽  
Fault Tree ◽  
Heat Removal ◽  
Quantitative Measure ◽  
Critical Systems ◽  
Tree Model ◽  
Hierarchical Tree ◽  
Risk Assessment Models

Risk assessment provides information to support decision-making. Then, the confidence that can be put in its outcomes is fundamental, and this depends on the accuracy, representativeness and completeness of the models used in the risk assessment. A quantitative measure is needed to assess the credibility and trustworthiness of the outcomes obtained from such models, for decision-making purposes. This article proposes a four-level, top-down, hierarchical tree to identify the main attributes and criteria that affect the level of trustworthiness of models used in risk assessment. The level of trustworthiness (Level 1) is broken down into two attributes (Level 2), three sub-attributes and one “leaf” attribute (Level 3), and seven basic “leaf” sub-attributes (Level 4). Based on this hierarchical decomposition, a bottom-up, quantitative approach is employed for the assessment of model trustworthiness, using tangible information and data available for the basic “leaf” sub-attributes (Level 4). Analytical hierarchical process is adopted for evaluating and aggregating the sub-attributes, and Dempster–Shafer theory is adopted to consider the uncertainty and the inconsistency in the experts’ judgments. The approach is applied to a case study concerning the modeling of the residual heat removal system of a nuclear power plant, to compute its failure probability. The relative trustworthiness of two mathematical models of different complexity is evaluated: a fault tree and a multi-states physics-based model. The trustworthiness of the multi-states physics-based model is found to outweigh that of the fault tree model, which can be explained by the fact that multi-states physics-based model takes into account the components failure dependency relations and degradation effects. The feasibility and reasonableness of the approach are, thus, demonstrated, paving the way for its potential applicability to inform decision-making on safety-critical systems.

An Analytical Model for Evaluating Wind Turbine Types

2014 ◽  
Vol 543-547 ◽  
pp. 333-336 ◽  
Author(s):  
Amy H.I. Lee ◽  
Meng Chan Hung ◽  
W.L. Pearn ◽  
He Yau Kang
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Evaluation Model ◽  
Renewable Energy Sources ◽  
Multiple Criteria Decision Making ◽  
Analytic Network Process ◽  
Renewable Energy Resources ◽  
Network Process ◽  
Term Energy

With worldwide developments stressing the security, economy, human well-beings and environmental costs of relying heavily on fossil and nuclear energy, the demand of safe renewable energy resources is expanding consistently and tremendously in recent years. With its safe and environmental characteristics, wind energy production has become one of the fastest growing renewable energy sources in the world. While new wind power capacity is being added in more places in various countries, the installation of wind turbines is an important process for long-term energy generation. In this study, an evaluation model, which incorporates multiple criteria decision making (MCDM) methods, including decision making trial and evaluation laboratory (DEMATEL) and fuzzy analytic network process (FANP), is developed to establish interactive relationships between criteria. Fuzzy Yager ranking method is used for deffuzification. The final ranking of the alternatives is obtained, and this can provide decision-makers for references.

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.

scholarly journals Application of AHP-GRA in safety evaluation of blasting flying stones

2021 ◽  
pp. 19
Author(s):  
Keyword(s):  
Evaluation Model ◽  
Safety Evaluation ◽  
Correlation Method ◽  
Warning Signal ◽  
First Grade ◽  
Evaluation Index ◽  
Practical Significance ◽  
Risk Level ◽  
Safety Level ◽  
Correlation Degree

Blasting flying stone is one of the six hazards in rock and soil blasting construction. In order to determine the risk level of blasting flying stone, 3 first-grade indexes such as blasting design and construction are selected, and 11 second-grade indexes such as warning range are not set, so as to establish the blasting flying stone safety evaluation model of AHP-GRA. The analytic hierarchy process (AHP) was used to calculate the weight of the evaluation index. The grey correlation method was used to determine the correlation degree between the blasting flying stone and the safety level of an airport. The risk level of an airport was calculated based on the weight of the evaluation index, and the engineering verification was carried out. The results show that there is no warning signal, no notice before detonation and the warning range is too small, which are the main factors of the flying stone accident. The model presented in this paper is used to evaluate the blasting flying stones in an airport, and the evaluation results are basically consistent with the reality. It can be seen that the evaluation model can scientifically and reasonably evaluate the risk level of blasting flying stones, which has important practical significance.

scholarly journals A Bayesian Network-Based Integrated for Flood Risk Assessment (InFRA)

2019 ◽  
Vol 11 (13) ◽  
pp. 3733 ◽  
Author(s):  
Hongjun Joo ◽  
Changhyun Choi ◽  
Jungwook Kim ◽  
Deokhwan Kim ◽  
Soojun Kim ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Bayesian Network ◽  
Disaster Management ◽  
Flood Risk ◽  
Principal Component ◽  
Assessment Method ◽  
Flood Damage ◽  
Flood Risk Assessment ◽  
Operating Characteristics ◽  
Analytic Hierarchy

Floods are natural disasters that should be considered a top priority in disaster management, and various methods have been developed to evaluate the risks. However, each method has different results and may confuse decision-makers in disaster management. In this study, a flood risk assessment method is proposed to integrate various methods to overcome these problems. Using factor analysis and principal component analysis (PCA), the leading indicators that affect flood damage were selected and weighted using three methods: the analytic hierarchy process (AHP), constant sum scale (CSS), and entropy. However, each method has flaws due to inconsistent weights. Therefore, a Bayesian network was used to present the integrated weights that reflect the characteristics of each method. Moreover, a relationship is proposed between the elements and the indicators based on the weights called the Integrated Index for Flood Risk Assessment (InFRA). InFRA and other assessment methods were compared by receiver operating characteristics (ROC)-area under curve (AUC) analysis. As a result, InFRA showed better applicability since InFRA was 0.67 and other methods were less than 0.5.

scholarly journals Study on Sustainable Development of the Transnational Power Grid Interconnection Projects under Diversified Risks Based on Variable Weight Theory and Bayesian Network

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Hao Wang ◽  
Yanan Jin ◽  
Xin Tan
Keyword(s):  
Risk Assessment ◽  
Sustainable Development ◽  
Power Grid ◽  
Assessment Method ◽  
Practical Significance ◽  
Weighting Method ◽  
Variable Weight ◽  
The Government ◽  
The Impact ◽  
Grid Interconnection

Transnational power grid interconnection is an important measure to promote the construction of energy Internet. It can meet the global power demand in a clean and green way, promote the UN’s concept of “sustainable energy,” and tackle climate changes. But, transnational power grid projects face many complex and variable risks due to their complex background and lacking experience. According to the characteristics of transnational power grid interconnection projects, a risk assessment index system including 10 indexes such as national relation, public participation, and available transmission capacity is constructed. Then, in order to overcome the shortcomings of traditional risk assessment methods, this paper proposes a risk assessment method combined with risk theory and probabilistic model, which can not only consider the uncertainties but also integrate the probability of accidents with consequences. Therefore, it can effectively assess the transnational power grid interconnection projects under diversified risks. In addition, in order to further magnify the impact of higher risks on such projects, a method combining traditional weighting method with the variable weight theory is proposed. The study in this paper provides certain guidance and decision-making support for different participants such as the government power sector, construction enterprises, and investment enterprises when they launch on sustainable development of the transnational project business, which have obvious practical significance.

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