A Bayesian network approach for predicting seismic liquefaction based on interpretive structural modeling

2015 ◽  
Vol 9 (3) ◽  
pp. 200-217 ◽  
Author(s):  
Ji-Lei Hu ◽  
Xiao-Wei Tang ◽  
Jiang-Nan Qiu
Keyword(s):  
Bayesian Network ◽  
Structural Modeling ◽  
Network Approach ◽  
Interpretive Structural Modeling ◽  
Seismic Liquefaction

scholarly journals Integration of Interpretive Structural Modeling with Fuzzy Bayesian Network for Risk Assessment of Tunnel Collapse

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Leping He ◽  
Tao Tang ◽  
Qijun Hu ◽  
Qijie Cai ◽  
Zhijun Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Analysis ◽  
Bayesian Network ◽  
Risk Model ◽  
Multicriteria Decision Making ◽  
Structural Modeling ◽  
Interpretive Structural Modeling ◽  
Construction Risk ◽  
Tunnel Collapse ◽  
The Relationship

Frequent collapse accidents in tunnels are associated with many construction risk factors, and the interrelationship among these risk factors is complex and ambiguous. This study’s aim is to clarify the relationship among risk factors to reduce the tunnel collapse risk. A multicriteria decision-making method is proposed by combining interpretive structural modeling (ISM) and fuzzy Bayesian network (FBN). ISM is used to determine the hierarchical relationships among risk factors. FBN quantitatively analyzes the strength of the interaction among risk factors and conducts risk analysis. The ISM-FBN method contains three steps: (1) drawing the ISM-directed graph; (2) obtaining the probability of the FBN nodes; and (3) using GeNle to implement risk analysis. The proposed method is also used to assess the collapse risk and detect the critical factors in the Canglongxia Tunnel, China. This method’s tunnel collapse risk model can provide managers with clear risk information and better realize project management.

Risk assessment by integrating interpretive structural modeling and Bayesian network, case of offshore pipeline project

2015 ◽  
Vol 142 ◽  
pp. 515-524 ◽  
Author(s):  
Wei-Shing Wu ◽  
Chen-Feng Yang ◽  
Jung-Chuan Chang ◽  
Pierre-Alexandre Château ◽  
Yang-Chi Chang
Keyword(s):  
Risk Assessment ◽  
Bayesian Network ◽  
Structural Modeling ◽  
Interpretive Structural Modeling ◽  
Offshore Pipeline ◽  
Pipeline Project

scholarly journals Factors Affecting the Lut Desert Tourism in Iran: Developing an Interpretive-Structural Model

2021 ◽  
Vol 13 (13) ◽  
pp. 7245
Author(s):  
Beniamino Murgante ◽  
Mohammad Eskandari Sani ◽  
Sara Pishgahi ◽  
Moslem Zarghamfard ◽  
Fatemeh Kahaki
Keyword(s):  
Sampling Method ◽  
Structural Model ◽  
Tourism Development ◽  
Cost Effective ◽  
Structural Modeling ◽  
Interpretive Structural Modeling ◽  
Factors Affecting ◽  
Purposive Sampling ◽  
Interpretive Structural Model ◽  
Lut Desert

The Lut desert is one of the largest and most attractive deserts in Iran. The value of desert tourism remains unclear for Iran’s economy and has only recently been taken into consideration by the authorities, although its true national and international value remains unclear. This study was aimed at investigating the factors that influence tourism development in the Lut desert. Data collected through the purposive sampling method was analyzed using Interpretive Structural Modeling and the MICMAC Analysis. According to the results, cost-effective travel expenses, security, and safety provided in the desert, together with appropriate media advertising and illustration of the Lut desert (branding) are the leading factors that influence tourism in the Lut desert in Iran. This paper highlighted the importance of desert tourism, especially in this region.

Analysis of third party reverse logistics provider using interpretive structural modeling

2012 ◽  
Vol 140 (1) ◽  
pp. 204-211 ◽  
Author(s):  
Kannan Govindan ◽  
Murugesan Palaniappan ◽  
Qinghua Zhu ◽  
Devika Kannan
Keyword(s):  
Reverse Logistics ◽  
Structural Modeling ◽  
Third Party ◽  
Interpretive Structural Modeling
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