Advances in Engineering Software
Bayesian networks for knowledge discovery in large datasets: basics for nurse researchers
Journal of Biomedical Informatics - Special issue: Building nursing knowledge through infomatics: from concept representation to data mining
Information Sciences: an International Journal - Special issue: Soft computing data mining
Credit rating analysis with support vector machines and neural networks: a market comparative study
Decision Support Systems - Special issue: Data mining for financial decision making
A Bayesian belief network for IT implementation decision support
Decision Support Systems
Decision trees for hierarchical multi-label classification
Machine Learning
Expert Systems with Applications: An International Journal
Large engineering project risk management using a Bayesian belief network
Expert Systems with Applications: An International Journal
A method based on distance measure for interval-valued intuitionistic fuzzy group decision making
Information Sciences: an International Journal
Using Bayesian networks for root cause analysis in statistical process control
Expert Systems with Applications: An International Journal
Intelligent fault inference for rotating flexible rotors using Bayesian belief network
Expert Systems with Applications: An International Journal
Evolutionary attribute ordering in Bayesian networks for predicting the metabolic syndrome
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
This paper presents a novel and systemic decision support model based on Bayesian Networks (BN) for safety control in dynamic complex project environments, which should go through the following three sections. At first, priori expert knowledge is integrated with training data in model design, aiming to improve the adaptability and practicability of model outcome. Then two indicators, Model Bias and Model Accuracy, are proposed to assess the effectiveness of BN in model validation, ensuring the model predictions are not significantly different from the actual observations. Finally we extend the safety control process to the entire life cycle of risk-prone events in model application, rather than restricted to pre-accident control, but during-construction continuous and post-accident control are included. Adapting its reasoning features, including forward reasoning, importance analysis and background reasoning, decision makers are provided with systematic and effective support for safety control in the overall work process. A frequent safety problem, ground settlement during Wuhan Changjiang Metro Shield Tunnel Construction (WCMSTC), is taken as a case study. Results demonstrate the feasibility of BN model, as well as its application potential. The proposed model can be used by practitioners in the industry as a decision support tool to increase the likelihood of a successful project in complex environments.