PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

High-Speed Rail (HSR) projects involve complex systems, huge investments and multidimensional risks. Effective risk reduction requires context-sensitive mitigation strategies which are accurate. The traditional entropy-based models are static and based on the subjective judgment of humans, and they lack adaptability in real-time modelling of the complexity of the HSR environment. The paper proposes an innovative integrated entropy-based risk assessment and mitigative framework, which is related specifically to HSR systems and will centre around dynamic gradations of risk weights and mitigation strategy. The framework presented is a series of 5 interconnected methodology blocks. First Dynamic Spatio-Temporal Entropy Weighting (DSTEW) generates its entropy weights, which are real-time adaptable timeline or temporal, e.g. seasonal, operational time-line factors, and spatial, i.e. zone-related variability. For checking the robustness of the procedure, Multi-Entropy Cross Validation (MECV) is used to check the consistency of subjective entropy estimates relating to the various spatial zones and time zones to retain only statistically consistent weight vectors. Entropy-Driven Bayesian Risk Adjustment (EDBRA) then adjusts and modifies these weights by including the history of past risk occurrences by means of Bayesian updating of risk. Subjective uncertainties are also resolved by using Hybrid Fuzzy-Entropy Multi-Criteria Prioritisation (HFEMCP), which uses the system of fuzzy logic in its consideration of the recalibrated weights and thus generates risk matrices of prioritised risks. Lastly, Entropy Resilient Networks Modelling (ERNM) produces inter-risk influence networks in which mitigation strategies are determined in a global way based on the various centralities which are derived from the entropy weighting procedures. The simulation results feature a quantum leap in improvements that include 10% to 15% improvements in weighting accuracy, validation consistency >95% and systemic resilience improvements of 20% to 30%. Thereby allowing for an adaptive, evidence-based, system-wide risk reduction planning of risk in HSR projects.