机场应急救援的规模决策与资源调配研究
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摘要
在综合交通运输体系中,民航运输业受天气影响严重,加上事故发生后人员极低的生还率和较大的社会影响,民航安全问题尤为引人注目。机场是处置民航突发事件、实施应急救援工作的主体。因此,借助先进的信息化技术建立稳定高效的机场应急救援系统是提高机场应急救援能力的迫切需要。本文分别对机场应急救援系统中两个关键性问题进行了深入研究,分别为机场应急救援的规模决策问题和救援资源的动态调配问题。
机场应急救援的规模决策对于抢救生命财产至关重要。针对目前救援规模决策缺乏合理规则指导的问题,提出了一种基于满意度控制的数据挖掘方法。该方法通过分析机场应急救援的总目标,根据满意度理论构造异样样本识别的满意度评价模型,并将满意度评价模型中的选择函数和拒绝函数植入数据挖掘的Apriori关联规则算法中,在保持样本完好性的同时识别异样数据,控制挖掘进程,最终能够建立有效的机场应急救援规模决策规则库,用以辅助决策者做出更为科学合理的决策。通过算法实例证明,基于满意控制的数据挖掘算法能更加有效地挖掘出合理的应急救援规模决策规则,提高挖掘的准确度和效率。
机场应急资源调配系统结构复杂,影响因素多,开放性强,随机及不确定因素多,因此引入Agent技术。鉴于Agent对不断变化的环境的适应性和求解问题的自主性,以及Agent间的相互合作和协调的特性,本文建立了基于多Agent技术的机场应急资源调配系统。首先根据从功能实体到Agent的映射方法,抽象出构成机场应急资源调配多Agent系统的个体Agent;对个体Agent的模型结构、功能模块以及系统工作方式作了深入的分析;在分析个体Agent模型基础上,进一步研究资源调配过程中个体Agent之间的协同工作过程,最终构建基于多Agent系统的机场应急资源调配体系框架。
In the comprehensive transportation system, the safety of aviation was usually paid most attention to, because the aviation transportation industry was affected by the weather, which has very little survivorship rate and great influence. The airdrome is the major place where aviation emergency accidents happen and emergency rescue work is carried out. Therefore, it is urgent required of establishing airport emergency rescue system to enhance the ability of airport emergency rescue by advanced information technology. This article does research on two essential issues: the scale decision-making of the airport emergency rescue and the rescue resource allocation.
The scale decision-making of the airport emergency rescue operation is extremely important to save the people and property. In allusion to the absence of reasonable rule guidance in the current rescue scale decision-making, this article puts forward a data mining method based on the satisfaction control. According to the overall objective of the airport emergency rescue and the satisfaction theory, the method constructs the satisfaction evaluation model for identifying abnormal sample, and then plants the selection function and the rejection function of the satisfaction evaluation model into Apriori Association Rule Algorithm of the data mining. It tries to identify the abnormal data with keeping the integrity of the sample and control the mining process. Finally, it establishes an effective assistant decision-making rule base of the airport emergency rescue for the decision maker to make a more reasonable decision. The algorithm example shows that it can obtain more reasonable rules of emergency rescue scale decision-making, increasing the mining accuracy and efficiency.
Airport emergency resource allocation system has complex structure, many factors, openness, random and strong uncertainty. In view of the Agent characteristics of adaptability to constantly changing environment, autonomy of solving problems, mutual cooperation and coordination between the Agents, this article establishes the rescue resource recombined Multi-Agent System. Firstly, According to a mapping method from the functional entity to the Agent, it abstracts out the allocation of resources constitute the Individual Agent of the Multi-Agent System; analyzes the model structure, functional module and system working model of the Individual Agent; finally, establish the Multi-Agent System framework of the airport emergency rescue resource allocation, Based on the further research of the collaborative work process between the Individual Agents.
机场应急救援的规模决策对于抢救生命财产至关重要。针对目前救援规模决策缺乏合理规则指导的问题,提出了一种基于满意度控制的数据挖掘方法。该方法通过分析机场应急救援的总目标,根据满意度理论构造异样样本识别的满意度评价模型,并将满意度评价模型中的选择函数和拒绝函数植入数据挖掘的Apriori关联规则算法中,在保持样本完好性的同时识别异样数据,控制挖掘进程,最终能够建立有效的机场应急救援规模决策规则库,用以辅助决策者做出更为科学合理的决策。通过算法实例证明,基于满意控制的数据挖掘算法能更加有效地挖掘出合理的应急救援规模决策规则,提高挖掘的准确度和效率。
机场应急资源调配系统结构复杂,影响因素多,开放性强,随机及不确定因素多,因此引入Agent技术。鉴于Agent对不断变化的环境的适应性和求解问题的自主性,以及Agent间的相互合作和协调的特性,本文建立了基于多Agent技术的机场应急资源调配系统。首先根据从功能实体到Agent的映射方法,抽象出构成机场应急资源调配多Agent系统的个体Agent;对个体Agent的模型结构、功能模块以及系统工作方式作了深入的分析;在分析个体Agent模型基础上,进一步研究资源调配过程中个体Agent之间的协同工作过程,最终构建基于多Agent系统的机场应急资源调配体系框架。
In the comprehensive transportation system, the safety of aviation was usually paid most attention to, because the aviation transportation industry was affected by the weather, which has very little survivorship rate and great influence. The airdrome is the major place where aviation emergency accidents happen and emergency rescue work is carried out. Therefore, it is urgent required of establishing airport emergency rescue system to enhance the ability of airport emergency rescue by advanced information technology. This article does research on two essential issues: the scale decision-making of the airport emergency rescue and the rescue resource allocation.
The scale decision-making of the airport emergency rescue operation is extremely important to save the people and property. In allusion to the absence of reasonable rule guidance in the current rescue scale decision-making, this article puts forward a data mining method based on the satisfaction control. According to the overall objective of the airport emergency rescue and the satisfaction theory, the method constructs the satisfaction evaluation model for identifying abnormal sample, and then plants the selection function and the rejection function of the satisfaction evaluation model into Apriori Association Rule Algorithm of the data mining. It tries to identify the abnormal data with keeping the integrity of the sample and control the mining process. Finally, it establishes an effective assistant decision-making rule base of the airport emergency rescue for the decision maker to make a more reasonable decision. The algorithm example shows that it can obtain more reasonable rules of emergency rescue scale decision-making, increasing the mining accuracy and efficiency.
Airport emergency resource allocation system has complex structure, many factors, openness, random and strong uncertainty. In view of the Agent characteristics of adaptability to constantly changing environment, autonomy of solving problems, mutual cooperation and coordination between the Agents, this article establishes the rescue resource recombined Multi-Agent System. Firstly, According to a mapping method from the functional entity to the Agent, it abstracts out the allocation of resources constitute the Individual Agent of the Multi-Agent System; analyzes the model structure, functional module and system working model of the Individual Agent; finally, establish the Multi-Agent System framework of the airport emergency rescue resource allocation, Based on the further research of the collaborative work process between the Individual Agents.
引文
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[2]中国民航局,民用航空飞行事故汇编[R],北京中国民航局,2002
[3]国际民航组织,ICAO卷1第1版,1990年7月
[4]中国民航局,民用运输机场应急救援规则,2000.4.3,90号令
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[7] Auerbach, H. Cost-effectiveness analysis of telemedical devices for pre-clinical traffic accident emergency rescue in Germany [J]. Technology and Health Care, 2006, 14(3):189-197.
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[9] Cohn. Campbell. Minimum Needs for Airport Fire Fighting and Rescue Services. Report: 7113, FAAAS-71-1, 1971. 97.
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[17] Richard Choularton. Complex learning: orgnizational learning from disasters.Safety Science, 2001, 39: 61-70.
[18] Milan Janic. An asseeement of risk and safety in civil aviation.Journal of Air Transport Management, 2000, 6:43-50.
[19] MPHRobert J. Melton.Revising the rural hospital disaster plan: A role for the EMS system in managing the multiple casualty incident .Annals of Emergency Medicine.1981,10(1):39-44.
[20] James Fenn RN, Paul Rega MD,etc. Assessment of U.S. helicopter emergency medical services' planning and preparedness for disaster response.Air Medical Journal, 1999, 18(1):12-15.
[21] Lord. Integrated Emergency Management : The Roles of Federal, State and Local Government with Implications for Homeland Security. Safety Scientce, 2003, 29: 414-629.
[22] G.Derekenaris, J.Garofalakis, C.Makris, J.Prentzas, S.Sioutas, A.Tsakalidis. Integrating GIS,GPS and GSM technologies for the effective management of ambulances . Computers,Enviroment and Urban Systems, 2001, 25:267-278.
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[24]罗帆,佘廉,平芸.民航机场灾害预警管理系统探讨[J].武汉理工大学学报,2002, 24(6):41-44
[25]罗帆,平芸,甘相田.民航灾害应急救援组织体系与联动程序探讨[J].中国管理科学,2006,10
[26]迟文学,孙刚,武峥.基于GIS民航应急救援与辅助决策支持系统研究[J].交通与计算机工程.2005,23(6):46-48
[27]朱新平,韩松臣,汪东生.机场应急救援系统软件架构的设计[J].武汉理工大学学报,2007,11
[28]姜静逸,韩松臣,汤新明,倪金霞,崔国山.基于满意控制的机场应急救援决策规则的数据挖掘[J].应用科学学报,2009, 27(6):644-650
[29] Jiang Jingyi, Han Songchen, and Tang Xinming,The Satisfaction Degree Control Mining Method Applied in the airport emergency rescue scale decision-making, 2009 international Symposium on Computational Intelligence and Design, Volume 1, 12-14 December 2009, Pages 91-95
[30] Fayyad U.M., Piatetsky-shapiro G, Smyth P., The KDD Process for extracting useful knowledge from volumes data . Communication of the ACM, 1996, 39(11):27-35.
[31] Frawley W.J., Piatetsky-shapiro G., Christopher Matheus, Knowledge Discovery in Databases: An Overview. In Piatetsky-shapiro G. and Christopher Matheus, (eds.), Knowledge Discovery in Databases, AAAI/MIT Press.1991,1-30.
[32] Fayyad U.M., Piatetsky-shapiro G., Smyth P., From Data Mining to Knowledge Discovery: An Overview. In Advances in Knowledge Discovery and Data Mining, AAAI/MIT Press, Cambridge Mass.,1996.
[33]任平.优化理论中的令人满意准则.模糊数学.1983:111-112
[34]金炜东.线性满意度及其组合运算.铁道学报.1997,19(5):49-55
[35] Simon H.A.现代决策理论的基石[M].杨砾译,北京:北京经济学院出版社,1989
[36]邹和礼,赵暑生,张龙祥.基于定量与定性指标综合分析的工程项目评标方法[J].铁道学报,2000, 22(6):112-115
[37] Doc9137, Airport Services Manual. Part 1 Rescue and Fire Fighting [M], International Civil Aviation Organization, Third edition-1990
[38] Shawe—Taylor J, De—Bie T, Cristianini N. Data mining, data fusion and information management [J]. IEE Proceedings Intelligent Transport Systems, 2006, 153(3): 221-229
[39] Agrawal R etal. Fast algorithms for mining association rules in large daltabases. In Proc. 20st Int. Conf. Very large Databases, 1994:478~499
[40] Srikant R and Agrawal R. Mining generalized association rules. In Prc. 21st Int. Conf. Very large Databases, 1995:407~419
[41]宋卫林.基于最大频繁项目集的数据挖掘关联规则算法研究,[博士学位论文].北京:北京邮电大学,2006
[42]彭斌.基于关联规则的基因芯片数据挖掘与应用,[博士学位论文].重庆:第三军医大学,2006
[43] Fayyad U.M. ,etal.Advances in Knowledge Diseovery and Data Mining.Cambridge,MA: AAAI/MITT Press,1996
[44]贾彩燕,陆汝钤.关联规则挖掘的取样误差量化模型和快速估计算法[J].计算机学报,2006, 29(4): 625-634.
[45]李军,郭强,刘建新.组合运输的优化调度[J].系统工程理论与实践,2001,2:117~121
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