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机构地区:[1]中国科学院上海高等研究院,上海201210 [2]上海交通大学中美物流研究院,上海200030 [3]华东理工大学信息科学与工程学院,上海200237
出 处:《中国管理科学》2014年第7期76-81,共6页Chinese Journal of Management Science
基 金:上海市科学技术委员会资助课题(12ZR1415200);教育部人文社会科学研究项目青年基金资助项目(10YJCZH180);国家自然科学基金资助项目(60903186;70732003);上海市信息安全综合管理技术研究重点实验室开放课题(AGK2012008)
摘 要:应急事件的演化和应急领域的脆弱性指标变化有着密切关系。大型运作系统核心能力受损后的应急期间,管理者非常关心如何根据动态变化的受损情况把握关键指标因素进行恢复,从而降低应急管理成本。本文基于知识库对应急领域知识结构进行分析,并将层级时序记忆方法引入应急脆弱性指标知识挖掘体系,通过脆弱性态势感知解决了指标约简问题,最后给出了构建知识库的推理机设计和推理算法。本文得到有助于应急管理的结论:基于知识库的脆弱性指标体系可动态分析突发事件和应急管理中蕴涵的知识,有助于对应急事件演化机理准确把握,提高应对效率。In this paper, vulnerability index infrastructure of disruption area is constructed based on knowledge base theory, to solve the problem that vulnerability of disruption is difficult to be described or understood by computer. Firstly, vulnerability index infrastructure is analyzed based on knowledge base, and vulnerability perception structure is constructed under disruption environment, multiple dimensions vulnerability data source are from multiple levels of supply chain in scene of disruption scenarios, the whole construction processing cover 3 parts: index extraction, features evaluation and situational awareness. Then, vulnerability index knowledge is mined with HTM (Hierarchical Temporal memory) method, which contributes to simplify index description with vulnerability situational awareness. Finally, inference machine design and inference algorithm are given to construct the knowledge base. The research shows that there is close relationship between evolution of disruption events and changes of disruption area vulnerability index infrastructure, with this vulnerability index infrastructure, explicit knowledge contained in disruption events and tacit knowledge contained in disruption management can be dynamically analyzed based on knowledge base. It contributes to manager's decision in recovering disruption with key factors accurately and dynamically, and reducing cost of disruption management, improve response efficiency.
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