| With the full implementation of China’s "Yangtze River Economic Belt" strategy and the operation of the 12.5-meter deep-water channel project below the Nanjing waters,the traffic flow of inland water vessels continues to increase,and the trend of large-scale vessels becomes increasingly apparent.Therefore,the complex navigation environment leds to a sharp growth in the number of water traffic accidents,which puts forward higher requirements for the emergency rescue work on inland waters.At the same time,the emergency resources play a vital role in the development of emergency response work on the water.If all kinds of emergency resources can be allocated scientifically and reasonably,it can not only improve the work efficiency and service level of emergency assistance,but also effectively avoid idle and waste of emergency resources.Facing the increasingly severe water security situation,in order to enhance the capacity of inland river emergency support,this article takes the water in the Nantong jurisdiction of the Yangtze River as an example to carry out a study on the allocation of water emergency resources.The purpose is to improve the efficiency and level of emergency rescue work in the river,and to reduce human casualties,property damage and environmental pollution caused by water traffic accidents.Thus,the stable operation of the inland navigation order is guaranteed to a certain extent.This article conducts some related research work in the following three aspects:First of all,this article sorts out the basic research theories related to emergency resource allocation.From the perspective of inland water traffic accident theory,its definition,classification,grade and characteristics are described in detail,which lays the foundation for the research contents such as the definition of water risks and the selection of emergency demand points.Meanwhile,this paper mainly introduces the continuous point and discrete point location models in classic location theory,and the static and dynamic allocation connotations in resource allocation theory,providing a theoretical basis for the construction of subsequent mathematical models.Then,this paper builds an emergency base location model based on multi-objective optimization.Summarize the main factors that affect the location of inland river emergency bases,and take the risk of inland river waters,emergency response time,and water coverage as part of the constraints of the emergency base site optimization model.Comprehensively considering the fairness and efficiency of emergency assistance work,a multi-objective decision-making theory is used to construct an optimization model for the inland river emergency base site combination of comprehensive coverage and multiple coverage.The beetle algorithm is introduced to improve the particle swarm algorithm,and a site selection optimization model solution algorithm is designed.The optimized emergency base site layout plan is thus calculated.In the final,this paper designs an emergency resource allocation model based on static demand.According to the classification and importance of the emergency resources on the water,the types of emergency resources studied are determined.Analyze the existing specifications related to emergency resource allocation requirements,and point out their unreasonableness.The grey neural network is used to predict the number of future traffic accidents.This paper calculates the resource allocation adjustment coefficients based on the natural environment and the traffic environment,then builds an emergency resource allocation model under static demand,and uses the information entropy theory to further determine the resource allocation schemes of different emergency bases.The research and design of emergency resource allocation schemes in busy inland waters can not only improve the utilization rate of resources,but also provide theoretical references and solutions for the competent departments of emergency rescue on the water.It is even a useful exploration of theoretical research in the field of emergency resource allocation. |