DocumentCode :
3002439
Title :
Shandong Peninsula dry & bulk cargo resource allocation research based on the maximum entropy and intelligent neural network
Author :
Xu, Zhao ; Peng, Liu ; Sibo, Liu
Author_Institution :
Transp. Manage. Coll., Dalian Maritime Univ., Dalian
fYear :
2008
fDate :
1-3 Sept. 2008
Firstpage :
2619
Lastpage :
2624
Abstract :
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.
Keywords :
freight handling; logistics; maximum entropy methods; neural nets; Shandong Peninsula; bulk cargo resource allocation research; dry cargo resource allocation research; flow distribution matrix; intelligent neural network; maximum entropy method; port industry; static traffic demand models; Construction industry; Demand forecasting; Entropy; Industrial control; Intelligent networks; Neural networks; Predictive models; Resource management; Telecommunication traffic; Traffic control; dry & bulk cargo; maximum entropy; neural network forecast;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-2502-0
Electronic_ISBN :
978-1-4244-2503-7
Type :
conf
DOI :
10.1109/ICAL.2008.4636614
Filename :
4636614
Link To Document :
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