基于公众偏好大数据分析的重大突发事件应急决策方案动态调整方法

doi:10.12005/orms.2020.0170

摘要/Abstract

摘要： 针对在重大突发事件应急过程中如何根据与其相关的公众偏好大数据信息来对事件进行划分以及确定事件风险大小等问题,提出了一种基于公众偏好大数据分析的两阶段聚类算法,将事件现场公众在社交媒体上发布的偏好大数据信息进行聚类分析,识别出多个与事件相关的子事件,并得出每个子事件的客观风险级别。然后,结合专家经验判断,综合得出每个子事件的风险级别,进而选择相对应的方案。在此基础上,根据实际突发事件多阶段演变特点,描述了应急决策中多事件多方案的动态调整过程,考虑方案之间的相关性和不同子事件调整方案对各风险级别子事件的应急处置效果、应对损失以及不同方案之间的转化成本等因素,得出不同情境下的最佳调整方案。通过案例分析说明了该方法的可行性和有效性。

关键词: 大数据, 应急决策, 子事件, 风险级别, 方案调整

Abstract: Aiming at the issues of how to divide events and determine the risk of events according to the related public preference information during the process of outsize emergencies, this paper proposes a two-stage clustering algorithm based on public preference big data information. Public preference information about the events published on social media is used for cluster analysis to identify several sub-events related to the event and derive the objective risk level of each sub-event. Then, combined with the experts' experience and judgment, the risk level of each sub-event is comprehensively obtained, and then the corresponding alternative is selected. On this basis, according to the characteristics of the multi-stage evolution of emergency, the dynamic adjustment process of multi-event and multi-altenative in emergency decision-making is described. Considering the correlation between the alternatives, the effects of emergency treatment for sub-events at different levels, and the capacity of dealing with loss, as well as the conversion costs between different programs and other factors, the best adjustment alternative under different scenarios can be obtained. The feasibility and effectiveness of this method are illustrated through case studies.

Key words: big date, emergency decision-making, sub-incident, risk level, plan adjustment

中图分类号:

C934

徐选华, 刘尚龙, 陈晓红. 基于公众偏好大数据分析的重大突发事件应急决策方案动态调整方法[J]. 运筹与管理, 2020, 29(7): 41-51.

XU Xuan-hua, LUI Shang-long, CHEN Xiao-hong. Dynamic Adjustment Method of Emergency Decision Scheme for Major Incidents Based on Big Data Analysis of Public Preference[J]. Operations Research and Management Science, 2020, 29(7): 41-51.

参考文献

[1] Asimakopoulou E, Bessis N, et al. Advanced ICTs for disaster management and threat detection: collaborative and distributed frameworks[J]. Reference & Research Book News, 2010, 25(4): 46-64.
[2] Liu S B, Palen L, Sutton J, et al. In search of the bigger picture: the emergent role of on-line photo sharing in times of disaster[M]//Proceedings of the Information Systems for Crisis Response and Management Conference (ISCRAM). 2008: 140-149.
[3] Vieweg S, Hughes A L, Starbird K, et al. Microblogging during two natural hazards events: what twitter may contribute to situational awareness[C]//Sigchi Conference on Human Factors in Computing Systems. ACM, 2010: 1079-1088.
[4] Yates D, Paquette S. Emergency knowledge management and social media technologies: a case study of the 2010 Haitian earthquake[J]. International Journal of Information Management, 2010, 47(1): 1-9.
[5] Terpstra T, Vries A D, Stronkman R. Towards a real-time twitter analysis during(flood)crises for operational(flood)crisis management[M]//Comprehensive Flood Risk Management. 2012: 1-9.
[6] 侯俊丽,杨巧.微博传播、公众参与和电子政务——以7·23温州动车事故为例[J].市场周刊:理论研究,2016(8):121-123.
[7] 袁靖华,郝文琦.中美政府社交媒体的公共危机传播比较研究——以天津爆炸、波士顿爆炸等突发公共危机事件的传播为例[J].浙江传媒学院学报,2016,23(4):22-32.
[8] 王刚桥,刘奕,杨盼,等.面向突发事件的复杂系统应急决策方法研究[J].系统工程理论与实践,2015,35(10):2449-2458.
[9] 李国杰.大数据研究的科学价值[J].中国计算机学会通讯,2012,8(9):8-15.
[10] Ginsberg J, Mohebbi M H, Patel R S, et al. Detecting influenza epidemics using search engine query data[J]. Nature, 2009, 457(7232): 1012-1014.
[11] Usharani P. Fast algorithms for mining association rules In datamining[J]. International Journal of Scientific & Technology Research, 2013, 23(3): 21-30.
[12] 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.
[13] Altay N, Green W G I . OR/MS research in disaster operations management[J]. European Journal of Operational Research, 2006, 175(1): 475-493.
[14] 杨静,陈建明,赵红.应急管理中的突发事件分类分级研究[J].管理评论,2005,17(4):37-41.
[15] Salton G, Wong A, Yang C S. A vector space model for automatic indexing[J]. Communications of the ACM, 1975, 18(11): 613-620.
[16] 黄承慧,印鉴,侯昉.一种结合词项语义信息和TF-IDF方法的文本相似度量方法[J].计算机学报,2011,34(5):856-864.
[17] 徐建民,王金花,马伟瑜.利用本体关联度改进的TF-IDF特征词提取方法[J].情报科学,2011(2):279-283.
[18] Kohonen T, Kaski S, Lagus K, et al. Self organization of a massive document collection[C]//IEEE Transactions on Neural Networks, 2000: 574-585.
[19] Rauber A, Merkl D. Using self-organizing maps to organize document archives and to characterize subject matters: how to make a map tell the news of the world[M]//Database and Expert Systems Applications. Springer Berlin Heidelberg, 1999: 302-311.
[20] Merkl D. Exploration of document collections with self-organizing maps: a novel approach to similarity representation[M]//Principles of Data Mining and Knowledge Discovery. Springer Berlin Heidelberg, 1997. 101-111.
[21] Dittenbach M, Merkl D, Rauber A. Hierarchical clustering of document archives with the growing hierarchical self-organizing map[J]. Lecture Notes in Computer Science, 2001, 2130(2): 500-505.
[22] Rauber A, Merkl D, Dittenbach M. The growing hierarchical self-organizing map: exploratory analysis of high-dimensional data[J]. IEEE Transactions on Neural Networks, 2002, 13(6): 1331-1341.
[23] 徐建锁,王正欧,王莉.一种基于自组织神经网络的中文文本聚类新方法[J].情报学报,2003,22(6):676-680.
[24] 张毓敏,谢康林.基于SOM算法实现的文本聚类[J].计算机工程,2004,30(1):75-76.
[25] Manning C D, Raghavan P, Schütze H. An introduction to information retrieval[M]. Cambridge University Press, 2009: 292-297.
[26] 国家科委国家计委国家经贸委自然灾害综合研究组.中国自然灾害区划研究的进展[M].海洋出版社,1998.
[27] 李开忠.中国洪水灾害损失风险评估[D].中国科学院研究生院博士论文,2011.
[28] 张乐波,金丹霞.粉尘涉爆企业危险级别分析研究[J].消防界(电子版),2017(2):12-13.
[29] 赵东风,陈爽,赵志强.基于脆弱性的油气管道风险评估及其应用[J].中国安全科学学报,2014,24(7):57-62.
[30] 郭琦,黄佳祺,张扬.基于改进AHP法的国外水电EPC项目风险评价研究[J].工程研究-跨学科视野中的工程,2017,9(6):609-615.
[31] Pohl D, Bouchachia A, Hellwagner H. Supporting crisis management via sub-event detection in social networks[C]//IEEE, International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises. IEEE, 2012: 373-378.
[32] 姜艳萍,樊治平,苏明明.应急决策方案的动态调整方法研究[J].中国管理科学,2011,19(5):104-108.
[33] 殷洁,戴尔阜,吴绍洪.中国台风灾害综合风险评估与区划[J].地理科学,2013,33(11):1370-1376.
[34] 刘毅,黄建毅,马丽.基于DEA模型的我国自然灾害区域脆弱性评价[J].地理研究,2010,29(7):1153-1162.
[35] 张云龙,刘茂.应急救援中的应急决策[J].中国公共安全: 学术版,2009(1):66-69.