Shandong Peninsula dry & bulk cargo resource allocation research based on the maximum entropy and intelligent neural network

With the development of international dry & bulk cargo market, international dry & bulk cargo seaborne trade is increasing rapidly, many kinds of dry & bulk cargo terminals were built along our countrypsilas coast, there even appears the problems of repeated constructions and fierce competition among these ports leading to an lower utilization efficiency with our coastline resources. Under such circumstances, how to effectively allocate dry & bulk cargo resources in one region, to control portspsila blind extension and how to promote the coordination and development in regional port cluster, in order to prevent the repetitive construction, and promote fair competition, these are important problems for the development of port industry. Take Shandong Peninsula as an example, this paper uses maximum entropy method to establish effective static traffic demand models, then using intelligent neural network model to forecast dry & bulk cargo flow distribution matrix of Shandong Peninsula port cluster. Forecast result can be used to guide berth planning, resource allocation and so on.