主管:中国科学院
主办:中国优选法统筹法与经济数学研究会
   中国科学院科技战略咨询研究院
论文

基于粒计算的非常规突发事件情景层次模型

展开
  • 大连理工大学管理与经济学部, 辽宁 大连 116024

收稿日期: 2015-08-28

  修回日期: 2016-06-02

  网络出版日期: 2017-03-22

基金资助

国家自然科学基金资助项目(71203019,71533001);辽宁省社科规划基金资助项目(L13DGL061);辽宁经济社会发展立项课题(2016lslktziglx-05);国土资源部黄土地质灾害重点实验室开放基金(KLGLAMLR201602)

Hierarchical Scenario Model of Unconventional Emergency Based on Granular Computing

Expand
  • Faculty of Management and Economics, Dalian University of Technology, Dalian 116024, China

Received date: 2015-08-28

  Revised date: 2016-06-02

  Online published: 2017-03-22

摘要

针对已有非常规突发事件情景表示模型与构建方法在支持多层次用户过程中所表现出来的不足,本文首先给出情景要素的形式化表示;在此基础上,给出基于粒计算非常规突发事件情景层次模型;给出情景泛化算法,实现低层次情景到高层次情景的泛化过程;最后通过一个算例探讨模型的应用过程,并论证其科学性及可行性。研究结果表明,基于粒计算给出非常规突发事件情景层次模型,可有效实现基于复杂、不确定情景信息快速生成满足不同层次应急管理用户需求的不同粒度情景结构。

本文引用格式

陈雪龙, 卢丹, 代鹏 . 基于粒计算的非常规突发事件情景层次模型[J]. 中国管理科学, 2017 , 25(1) : 129 -138 . DOI: 10.16381/j.cnki.issn1003-207x.2017.01.014

Abstract

To cover the shortages of existent scenario representation models and scenario construction methods for unconventional emergency in being used to support multi-level emergency management personnel, the formal representation of scenario elements is discussed firstly. Then, the hierarchical scenario model of unconventional emergency based on granular computing is proposed. Afterwards, the scenario generalization algorithm is put forward to realize the scenario generalization processes from low-level scenarios to up-level scenarios. In the end, an example is analyzed to illustrate the application process and to prove the scientificalness and the feasibility of the proposed model. The results show that the hierarchical scenario model of unconventional emergency based on granular computing can generate scenario structures of different granularities which can be used to support multi-level emergency management personnel on the basis of complex and uncertain scenario information.

参考文献

[1] 钟永光,毛中根,翁文国,等.非常规突发事件应急管理研究进展[J].系统工程理论与实践,2012,32(5):911-917.

[2] 华国伟,余乐安,汪寿阳.非常规突发事件特征刻画与应急决策研究[J].电子科学大学学报(社科版),2011,13(2):33-36.

[3] 李仕明,刘娟娟,王博.基于情景的非常规突发事件应急管理研究——"2009突发事件应急管理论坛"综述[J].电子科技大学学报(社科版),2010,12(1):1-3.

[4] 李仕明,张志英,刘樑,等.非常规突发事件情景概念研究[J].电子科技大学学报(社科版),2014,16(1):1-5.

[5] Dettinger M D, Ralph F M, Hughes M, et al. Design and quantification of an extreme winter storm scenario for emergency preparedness and planning exercises in California[J]. Natural Hazards, 2012, 60(3):1085-1111.

[6] Rivas-Medina A, Martínez-Cuevas S, Quirós L E, et al. Models for reproducing the damage scenario of the Lorca earthquake[J]. Bulletin of Earthquake Engineering,2014,12(5):2075-2093.

[7] 吴广谋, 赵伟川, 江亿平.城市重特大事故情景再现与态势推演决策模型研究[J].东南大学学报(哲学社会科学版),2011,13(1):18-23.

[8] 仲秋雁,郭艳敏,王宁,等.基于知识元的非常规突发事件情景模型研究[J].情报科学,2012,30(1):115-120.

[9] 武旭鹏,夏登友,李健行.非常规突发事件情景描述方法研究[J].中国安全科学学报,2014,24(4):159-165.

[10] 钱静,刘奕,刘呈,等.案例分析的多维情景空间方法及其在情景推演中的应用[J].系统工程理论与实践,2015,35(10):2588-2595.

[11] 刘德海,韩呈军,尹丽娟.城市拆迁群体性事件演化机理的多情景演化博弈分析[J].运筹与管理,2016,25(1):76-84.

[12] 方志耕,杨保华,陆志鹏,等.基于Bayes推理的灾害演化GERT网络模型研究[J].中国管理科学,2009,17(2):102-107.

[13] 杨保华,方志耕,刘思峰,等.基于GERTS网络的非常规突发事件情景推演共力耦合模型[J].系统工程理论与实践,2012,32(5):963-967.

[14] 周愉峰,马祖军. 基于情景推演的地震灾害演化动态GERT网络模型[J]. 自然灾害学报,2012,22(3):68-75.

[15] Prakash M, Kai R, Cleary P W. Modelling the impact of dam failure scenarios on flood inundation using SPH[J]. Applied Mathematical Modelling, 2014, 38(23):5515-5534.

[16] Hu Shaolong, Han Chuanfeng, Meng Lingpeng. A scenario planning approach for propositioning rescue centers for urban waterlog disasters[J]. Computers & Industrial Engineering, 2015, 87:425-435.

[17] 王循庆. 基于随机Petri网的震后次生灾害预测与应急决策研究[J]. 中国管理科学, 2014,22(11):159-165.

[18] Li Jian, Chen Changkun. Modeling the dynamics of disaster evolution along causality networks with cycle chains[J]. Physica A:Statistical Mechanics & Its Applications, 2014, 401:251-264.

[19] Yao Yiyu. Granular computing:Basic issues and possible solutions[C]//Proceedings of the 5th Joint Conference on Information Sciences. 2000, 1:186-189.

[20] Skowron A, Stepaniuk J. Information granules:Towards foundations of granular computing[J]. International Journal of Intelligent Systems, 2001, 16(1):57-85.

[21] Chen Guang, Zhong Ning, Yao Yiyu. A hypergraph model of granular computing[C]//Proceedings of the 2008. IEEE International Conference on. Granlar Computing,August 26-28, 2008:130-135.

[22] Bargiela A, Pedrycz W. Toward a theory of granular computing for human-centered information processing[J]. IEEE Transactions on Fuzzy Systems, 2008, 16(2):320-330.

[23] Yao Yiyu. Interpreting concept learning in cognitive informatics and granular computing[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B(Cybernetics), 2009, 39(4):855-866.

[24] 徐计,王国胤,于洪.基于粒计算的大数据处理[J].计算机学报,2015,38(8):1497-1517.

[25] Chen C L P, Zhang Chunyang. Data-intensive applications, challenges, techniques and technologies:A survey on big data[J]. Information Sciences, 2014,275:314-347.

[26] 苗夺谦,李德毅,姚一豫,等.不确定性与粒计算[M].北京:科学出版社,2011.

[27] 王国胤,张清华,胡军.粒计算研究综述[J].智能系统学报,2007,2(6):8-26.

[28] 余斌,马煜,吴雨夫.汶川地震后四川省绵竹市清平乡文家沟泥石流灾害调查研究[J].工程地质学报, 2010, 18(6):827-836.

[29] 马欢,张绍和,刘卡伟.泥石流运动参数的计算方法[J].西部探矿工程,2010,22(6):122-125.

[30] 刘希林,唐川,朱静,等.泥石流危险范围的流域背景预测法[J].自然灾害学报,1992,1(3):56-67.

[31] 张金山,谢洪.岷江上游泥石流堵河可能性的经验公式判别[J].长江流域资源与环境,2008, 17(4):651-655.

[32] 聂高众,高建国,苏桂武,等.地震应急救助需求的模型化处理[J].资源科学,2001,23(1):69-76.
文章导航

/