Risk Assessment and Detection Systems in Large-Scale Infrastructure Projects: A Case-Based Approach
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V5I2P119Keywords:
Infrastructure Projects, Risk Assessment, Qualitative Techniques, Quantitative Analysis, Risk MitigationAbstract
The nature of mega infrastructure projects is that they are prone to various risks due to technical, managerial, environmental and financial uncertainties. Cost, time, quality, safety, and sustainability-wise, project goals must be achieved through thorough risk assessment and mitigation. The review gives a thorough analysis of qualitative, quantitative and hybrid methods of construction risk analysis that are underway. Qualitative methods such as fuzzy logic systems, expert judgment and Delphi method help in the initial evaluation of the project where there are few numerical data. Quantitative approaches that lend themselves to mathematical estimates of risk impacts and decision-making accuracy include sensitivity analysis, decision trees, and Monte Carlo simulation. Simultaneously, the next-generation approaches based on the combination of machine-learning algorithms and Building Information Modelling (BIM) provide a better predictive value and visualization capabilities in real time in the framework of the complex infrastructure. The paper also discusses mitigation measures at the project planning, engineering controls and financial instruments with contexts on risk allocation, contingency planning, structural redundancy, regulatory compliance, construction insurance and hedging mechanisms. An example of a smart building project shows the practical implementation of these techniques based on a Decision Tree classifier to predict risks based on data, which has high precision, recall, and strength.
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