With the rapid development of the urbanization process, rainstorm water-logging events occur more frequently in big cities in China, which causes great impact on urban traffic safety and brings about severe economic losses. Water-logging has become a hot issue of widespread concern in China. As one kind of natural disasters and emergencies, rainstorm water-logging has the uncertainties of occurrence, development, and evolution. Thus, the emergency decision-making in rainstorm water-logging should be carried out in stages according to its development trend, which is very complicated. In this paper, an emergency decision-making method was proposed for urban water-logging with a hybrid use of dynamic network game technology, Bayesian analysis, and multi-attribute utility theory. The dynamic game process between “rainstorm water-logging” and “decision-making group” was established and the dynamic generation of emergency schemes was analyzed based on Bayesian analysis in various stages of water-logging. In terms of decision-making attributes, this paper mainly considered two goals, i.e., ensuring smooth traffic and controlling emergency cost. The multi-attribute utility theory was used to select the final scheme. An example analysis in Guangzhou of China showed that the method is more targeted and can achieve emergency management objectives more effectively when compared with traditional methods. Therefore, it can provide reference for the scientific decision-making of emergency management in urban rainstorm water-logging.
Multigranulation fuzzy rough set over two universes and its application to decision making
