Nabawy, M and Gouda Mohamed, A (2024) Risks assessment in the construction of infrastructure projects using artificial neural networks. International Journal of Construction Management, 24(4), pp. 361-373. ISSN 1562-3599
Abstract
Infrastructure Project (IP) construction in Egypt is saddled with copious risks emanating from the manque of risk knowledge, driving these projects to enigmatic failure concerning construction cost. The paper’s novel contribution is to acquaint with an Infrastructure Neural Risk Model (INRM) approach that colossally spotlights the substantial risk factors confronting Egypt’s IP construction apropos to Probability of Occurrence (POO) and Impact on Cost (IOC). Hundred and fifty-seven risk factors were compiled from the literature under three risk categories and reduced to 10, portraying the critical risk influencing the IP construction costs inconsolably. The paper’s main merits include identifying the puritanical risk factors impacting the IP construction costs and bestowing contractors with a paradigm for anticipating risk factors POO and their respective IOC among the IP. Five chronological steps constitute the developed approach inaugurating with (1) conducting a thorough analysis of risk management studies in the IP, (2) adopting a Risk Breakdown Structure (RBS), (3) implementing a checklist analysis to recall the substantial IP risks, (4) constituting a questionnaire survey to interrogate the forthcoming risk factors inferred from comprehensive prior research, and (5) developing INRM paradigm to anticipate the prospective risk factors post-mitigation impact on the construction cost. According to the findings, the coefficient of determination (R2) of the developed INRM unearthed the best INRM outcomes, and the optimal architecture in training and test datasets is 0.872 and 0.777, respectively.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | infrastructure projects; neural network; risk assessment; risk management |
| Index terms: | construction cost, risk factor, risk management, paradigm, risk assessment, infrastructure project, Egypt, risk breakdown structure, survey, artificial neural network, neural network, mitigation, questionnaire, dataset |
| Subjects: | risk assessment, data collection methods, modelling and simulation, financial and cost management, artificial intelligence, education and knowledge transfer, financial risk, Geography, data management, environmental hazards, infrastructure and transport systems |
| Topics: | Digital Applications, Sustainability, Risk Management, Research Practice, Geographical Context, Engineering Principles, Cost Management |
| Descriptive scope: | 5 PCTEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here