DEVELOPING A COMPREHENSIVE RISK ASSESSMENT MODEL BASED ON FUZZY BAYESIAN BELIEF NETWORK (FBBN)

2020 ◽  
Vol 26 (7) ◽  
pp. 614-634
Author(s):  
Li Guan ◽  
Qiang Liu ◽  
Alireza Abbasi ◽  
Michael J. Ryan

Reliable and efficient risk assessments are essential to deal effectively with potential risks in international construction projects. However, most conventional risk modeling methods are based on the hypothesis that risk factors are independent, which does not account adequately for the causal relationships among risk factors. In this study, a risk assessment model for international construction projects was developed to improve the efficacy of risk management by integrating fault tree analysis and fuzzy set theory with a Bayesian belief network. The risk rating of each risk factor, expressed as the product of risk occurrence probability and impact, was incorporated into the risk assessment model to evaluate degrees of risk. Therefore, risk factors were categorized into different risk levels taking into account their inherent causal relationships, which allowed the identification of critical risk factors. The applicability of the fuzzy Bayesian belief network-based risk assessment model was verified using a case study through a comparative analysis with the results from a fuzzy synthetic evaluation method. The comparison shows that the proposed risk assessment model is able to provide guidelines for an effective risk management process and ultimately to increase project performance in a complex environment such as international construction projects.

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tao Wang ◽  
Shangde Gao ◽  
Pinchao Liao ◽  
Tsenguun Ganbat ◽  
Junhua Chen

Purpose The purpose of this paper is to construct a two-stage risk management framework for international construction projects based on the meta-network analysis (MNA) approach. A plethora of international construction studies seems to assume risks as independent and therefore, risk intervention strategies are usually critiqued as ineffective. Design/methodology/approach In the risk assessment stage, a multi-tiered risk network structure was developed with the project objectives, risk events, risk factors and stakeholders, and critical risk factors were selected based on a series of calculations. In the risk intervention stage, targeted risk intervention strategies were proposed for stakeholders based on the results of the first stage. A highway construction project in Eastern Europe was selected as a case study. Findings The results showed that 17 risk factors in three categories – external, stakeholder-related and internal – are critical, and the project manager, construction management department, supplier and contract department are the most critical stakeholders that affect the entire project performance. Based on the critical risk factors and project stakeholders, targeted risk intervention strategies were proposed. The risk assessment results of MNA were found to be more reliable and consistent with the project conditions than the risk matrix method; the risk intervention strategies of MNA can effectively address project objectives. Originality/value This study modeled risk priorities based on risk associations and put forward a new method for risk management, supplementing the body of knowledge of international construction. The results of this study are of critical importance in management practices.


Facilities ◽  
2014 ◽  
Vol 32 (11/12) ◽  
pp. 624-646 ◽  
Author(s):  
Daniel W.M. Chan ◽  
Joseph H.L. Chan ◽  
Tony Ma

Purpose – This paper aims to develop a fuzzy risk assessment model for construction projects procured with target cost contracts and guaranteed maximum price contracts (TCC/GMP) using the fuzzy synthetic evaluation method, based on an empirical questionnaire survey with relevant industrial practitioners in South Australia. Design/methodology/approach – A total of 34 major risk factors inherent with TCC/GMP contracts were identified through an extensive literature review and a series of structured interviews. A questionnaire survey was then launched to solicit the opinions of industrial practitioners on risk assessment of such risk factors. Findings – The most important 14 key risk factors after the computation of normalised values were selected for undertaking fuzzy evaluation analysis. Five key risk groups (KRGs) were then generated in descending order of importance as: physical risks, lack of experience of contracting parties throughout TCC/GMP procurement process, design risks, contractual risks and delayed payment on contracts. These survey findings also revealed that physical risks may be the major hurdle to the success of TCC/GMP projects in South Australia. Practical implications – Although the fuzzy risk assessment model was developed for those new-build construction projects procured by TCC/GMP contracts in this paper, the same research methodology may be applied to other contracts within the wide spectrum of facilities management or building maintenance services under the target cost-based model. Therefore, the contribution from this paper could be extended to the discipline of facilities management as well. Originality/value – An overall risk index associated with TCC/GMP construction projects and the risk indices of individual KRGs can be generated from the model for reference. An objective and a holistic assessment can be achieved. The model has provided a solid platform to measure, evaluate and reduce the risk levels of TCC/GMP projects based on objective evidence instead of subjective judgements. The research methodology could be replicated in other countries or regions to produce similar models for international comparisons, and the assessment of risk levels for different types of TCC/GMP projects (including new-build or maintenance) worldwide.


Author(s):  
Kevin Cicansky ◽  
Glenn Yuen

This Paper presents the method TransCanada PipeLines uses to assess the integrity risks with respect to operating its high pressure natural gas pipelines. TransCanada PipeLines’ experiences, results and successes gained through the implementation of its risk program, TRPRAM (TransCanada Pipelines Risk Assessment Model) are highlighted.


2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e13092-e13092
Author(s):  
Michiyo Yamada ◽  
Takashi Ishikawa ◽  
Sadatoshi Sugae ◽  
Kazutaka Narui ◽  
Eiji Arita ◽  
...  

e13092 Background: No comprehensive breast cancer risk assessment model for Japanese women exists. Consequently, we have collected Japanese women’s data to investigate key BC risk factors with an objective of deriving a Japanese-women specific BC risk assessment model. Methods: We conducted a retrospective case-control study (paper-based with postal survey) at 15 institutions during 2014-2015. A survey was distributed to Japanese females aged 20-80 who had BC check-up. All pertinent data of a total of 34 factors including demographic and reproductive factors, social history and eating habits was collected. Cases and controls were divided into three groups respectively, premenopausal (PRE; 20 ≤ age < 45), perimenopausal (PERI; 45 ≤ age ≤ 55) and postmenopausal group (POST; 55 < age ≤ 80). Cases and control variables were compared by t-test, chi-square test and Wilcoxon rank sum test. Preliminary BC risk was calculated by logistic regression analysis. Results: A total of 3975 female Japanese datasets were collected, of which 2494 were complete (all variables present) with 1401 controls and 1093 cases were used. There were 222 cases and 332 controls for PRE, 404 cases and 537 controls for PERI, and 467 and 532 controls for POST. The univariate analysis demonstrated that BMI was significantly higher in cases than in controls in all groups (P < 0.01) as was “number of deliveries” in PRE and POST (P < 0.001) and Brinkman index in PRE and PERI (p = 0.017). Multivariate analysis revealed that BC risk was positively associated with BMI (OR 1.080, 95% CI 1.017–1.148, p = 0.012) in PRE, BMI (OR 1.121, 95% CI 1.072–1.174, p < 0.01) and brinkman index (OR 1.000005, 95% CI 1.000002–1.000008, p < 0.01) in PERI, age (OR 1.054, 95% CI 1.028–1.081, p < 0.010), BMI (OR 1.153, 95% CI 1.076-1.171, p < 0.01) and family history (OR 1.497, 95% CI 1.103–2.033, p = 0.001) in POST, while negatively associated with regular exercise (OR 0.672, 95% CI 0.517–0.873, p = 0.003) in POST. Conclusions: BMI in all groups, in addition, the Brinkman index in PERI and age and family history in POST are BC risk factors. Exercise is a protective risk factor in POST. However, the preliminary results are incomplete and further analysis will be conducted before a full risk assessment model is proposed for Japanese women.


Author(s):  
Jean Baptiste Ramampisendrahova ◽  
Andriamanantsialonina Andrianony ◽  
Aina Andrianina Vatosoa Rakotonarivo ◽  
Mamisoa Bodohasina Rasamoelina ◽  
Eric Andriantsoa ◽  
...  

The purpose of this research is to ascertain the prevalence of postoperative venous thromboembolism in the Department of Surgery at Anosiala University Hospital and to identify risk factors for developing postoperative venous thromboembolism using the Caprini Risk Assessment Model. From December 2017 to October 2019, this was a 22-month prospective cohort research conducted at Anosiala University Hospital. It included all adult patients over the age of 18 who were operated on in an emergency or on a planned basis by the Department of Surgery. This research included 662 participants. Within 30 days after surgery, the risk of venous thromboembolism was 0.3 percent. According to the overall Caprini score, 25.2 percent of patients were classified as having a low risk of venous thromboembolism, 25.2 percent as having a moderate risk, 29.5 percent as having a high risk, and 20.1 percent as having the greatest risk. Patients in the highest risk category (scoring 5) had a substantially increased chance of having venous thromboembolism after surgery (p = 0.0007). Only major open surgery was related with a statistically significant increase in postoperative venous thromboembolism (p = 0.028). Age 75 years, elective arthroplasty, and hip, pelvic, or leg fractures were not linked with postoperative venous thromboembolism statistically significantly (p> 0.05). Our findings indicate that the Caprini risk assessment model might be used successfully to avoid postoperative venous thromboembolism in surgical patients in Madagascar, since patients in the highest risk category had a considerably increased chance of developing postoperative venous thromboembolism.


Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1089
Author(s):  
Menglu Chen ◽  
Shaowei Ning ◽  
Juliang Jin ◽  
Yi Cui ◽  
Chengguo Wu ◽  
...  

In recent years, drought disaster has occurred frequently in China, causing significant agricultural losses. It is increasingly important to assess the risk of agricultural drought disaster (ADD) and to develop a targeted risk management approach. In this study, an ADD risk assessment model was established. First, an improved fuzzy analytic hierarchy process based on an accelerated genetic algorithm (AGA-FAHP) was used to build an evaluation indicator system. Then, based on the indicators, the ADD assessment connection numbers were established using the improved connection number method. Finally, the entropy information diffusion method was used to form an ADD risk assessment model. The model was applied to the Huaibei Plain in Anhui Province (China), with the assessment showing that, in the period from 2008 to 2017, the plain was threatened continuously by ADD, especially during 2011–2013. The risk assessment showed that southern cities of the study area were nearly twice as likely to be struck by ADD as northern cities. Meanwhile, the eastern region had a higher frequency of severe and above-grade ADD events (once every 21 years) than the western region (once every 25.3 years). Therefore, Huainan was identified as a high-risk city and Huaibei as a low-risk city, with Suzhou and Bengbu more vulnerable to ADD than Fuyang and Bozhou. Understanding the spatial dynamics of risk in the study area can improve agricultural system resilience by optimizing planting structures and by enhancing irrigation water efficiency. This model could be used to provide support for increasing agricultural drought disaster resilience and risk management efficiency.


Author(s):  
Gokcen Ogutcu

This study focuses on identification of risk factors in pipeline system and also, concentrates on identification of relationship between parameters. In order to achieve this purpose, Bayesian Belief Network with historical data was used to provide a framework for assessing risk relative to the company’s petroleum pipeline system. Each of the variables in the Bayesian Belief Network is described by nodes and each node has a state. Relationships between parameters are presented by arrows. Probability of any node being in state was shown in conditional probability tables. Historical data were helpful to build conditional probability tables. Variables were defined as corrosion, third party damage, mechanical and operational failure.


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