| 摘要: | 關鍵基礎設施對國家來說是重要的資產，用以連續地產生或輸送重要貨物或服務，例如交通設施、通訊設施、電力設施、瓦斯與汽油儲存與輸送設施、供水系統設施等。一般來說，基礎設施的擁有者為管控設施的正常運作會建立與維護基礎設施資料，這些資料包括地上或地下的管線與交通網路資訊等。此外，大部分關鍵基礎設施彼此是相依的，如供水系統需靠電力設施運作，此互動關係將建立跨越系統的複雜性。隨著國家關鍵基礎設施逐漸發展，系統複雜相依性將成長，國家的弱點將增加，也更易遭受威脅。例如某災害發生使得一關鍵基礎設施停止運作，關鍵基礎設施間的相依性將使得其他關鍵基礎設施也失效，惡化或擴大原災害造成的損害。事實上，研究顯示，完整與正確的基礎設施與其相依性資料對於建立災害管理系統來說非常重要。進一步的說，若政府沒有準確、即時、易取得的關鍵基礎設施與其相依性資料，則政府將很難降低天然或人為災害所造成的損害。儘管關鍵基礎設施與其相依性資料是如此重要，過去研究很少以完備方法論塑模關鍵基礎設施相依性，並設計整合式資訊模型，藉以了解一群關鍵基礎設施如何互動與工作，協助評估在災害下國家的弱點為何。本研究的重點在於分析與設計一整合式資訊模型，使其可用來描述關鍵基礎設施與其相依性資料，以供決策人員分析災害影響，與減緩災害造成的損害。本研究將使用UML 的擴充機制來塑模關鍵基礎設施的相依性，並設計出新的模型元素用以描述關鍵基礎設施資料。此外，因目前大部分的關鍵基礎設施資料均存放在GIS 系統內，但為分析災害發生與關鍵基礎設施的相依性，時間軸度的資料必須考慮進此新模型內，藉以完成時間相關的資料查詢。目前資料庫領域最先進的時空物件式資料庫技術為實現上述需求的可行方案之一。源自於軍事用數位戰場等技術，時空物件式資料庫可儲存隨著時間變化的物件資訊，並提供與時間相關的查詢介面，以動態屬性簡化資料同步程序。本研究將應用時空物件式資料庫技術，搭配關聯資料探勘應用到Leontief 投入產出模型，設計可供決策人員降低災害損害的整合式資訊模型，並開發雛型系統程式，收集實際關鍵基礎設施資料進行測試。本研究首先將回顧目前災害管理系統的文獻，接著將訪談交通單位官員與管線單位專家，設計新的具備時空處理能力之整合式資訊模型與雛型程式，並定義系統效能指標，最後並對此研究撰寫結論與建議。Critical infrastructure means important assets for producing or distributing a continuous flow of essential goods or services of a country. These assets include, but are not limited to, facilities for transportation, telecommunications, electric power systems, gas and oil storage and transportation, and water supply systems. Infrastructure baseline data, which are usually created and maintained by infrastructure systems owners for supervising the operations of the systems, contain above-ground and subsurface information for utility lines and transportation networks. Since most critical infrastructure systems interact, these interactions often create complex relationships, dependencies, and interdependencies that across infrastructure boundaries. As the complexity and interconnectedness of a country’s critical infrastructure evolve, threats and vulnerabilities for the country increase. When a disaster destroys one infrastructure system, the critical infrastructure interdependencies exacerbate the damage caused by the disaster. In fact, complete and accurate critical infrastructure baseline data and interdependencies are fundamental to create a disaster management system. Further, without accurate, timely, and accessible baseline data and interdependency information of critical infrastructure, a government can hardly help reducing the damage caused by natural or artificial disasters. However, past research does not use a comprehensive methodology to analyze the critical infrastructure baseline data and interdependencies. A comprehensive understanding of how networked critical infrastructure systems work can provide the means to better evaluate vulnerabilities related to hazards. The research analyzes and designs an integrated information model that is expected to best characterize the critical infrastructure interdependencies with baseline data for disaster mitigation. The extension mechanisms of Unified Modeling Language (UML) will be investigated and employed to derive new modeling elements that describe the critical infrastructure baseline data and interdependencies. In addition, since critical infrastructure baseline data, which have been mostly stored in Geographic Information Systems (GIS), also have substantial implications for temporal data processing, the proposed information model should accommodate the spatiotemporal data requirements. Hence, one advanced database technique that has emerged as a main focus of many spatial-temporal information systems such as the digital battlefield in the military is to keep track of object locations over time and to support temporal queries about future locations of the objects. Called Moving objects database (MOD) or Spatiotemporal Objects Database (SOD), this technique aims to deal with geometries changing over time and to simplify the data update process. The Leontief’s Input-Output model will be investigated to help create interdependencies of critical infrastructures. The association rules discovery technique will be utilized to help create the interdependency matrix. A literature review of current disaster management system (DMS) will be conducted, followed by several interviews with transportation agents and utility owners. The requirements of the model and prototype will be identified, and a pilot system will be created. Functional and non-functional requirements and measures will be determined and used to test the model and prototype, followed by conclusions and recommendations for the research. 研究期間 : 9808 ~ 9907 |
