Kybernetes, Journal Year: 2024, Volume and Issue: unknown
Published: Sept. 12, 2024
Purpose This research proposes a novel risk assessment model to elucidate the propagation process of industrial safety accidents triggered by natural disasters (Natech), identifies key factors influencing urban carrying capacity and mitigates uncertainties subjectivity due data scarcity in Natech assessment. Design/methodology/approach Utilizing disaster chain theory Bayesian network (BN), we describe cascading effects Natechs, identifying critical nodes system failure. Then propose an method using coefficient variation cloud BN, constructing indicator for infrastructure, population environmental capacity. The determines interval values indicators weights missing model. A case study from Pearl River Delta region validates Findings (1) Urban development relies heavily on (2) region’s social struggles cope with rapid growth. (3) There is significant disparity among cities, some trends contrary development. (4) Cloud BN outperforms classical Takagi-Sugeno (T-S) gate fuzzy describing real-world random situations. Originality/value present framework evaluating areas face Natechs. By developing that integrates models, addresses issue scarce objective reduces inherent previous studies relied expert opinions. results demonstrate proposed BNs.
Language: Английский