系统工程理论与实践
繫統工程理論與實踐
계통공정이론여실천
Systems Engineering—Theory & Practice
2015年
3期
743~750
,共null页
巨灾风险大数据 应急分类分解算法 应急分拣算法 事故灾难度 特大地震灾害
巨災風險大數據 應急分類分解算法 應急分揀算法 事故災難度 特大地震災害
거재풍험대수거 응급분류분해산법 응급분간산법 사고재난도 특대지진재해
catastrophe risk big data; emergency classification decomposition algorithm; emergency sorting algorithm; accidents disaster degree; devastating earthquake
本文主要研究巨灾风险大数据处理的应急分类、分解、分拣算法，给出了相应的算法原理和可操作的步骤．首先根据巨灾风险大数据灾害规模巨大的特征，提出了一种用来解决巨灾风险大数据中一级事件的应急分类与二级事件及以下更低级事件的应急分解算法，并以特大地震灾害作为实例进行了算法应用．接着定义了事故灾难度，用来对巨灾风险大数据处理过程中，对各种级别的事故灾难后果进行不同的数字标识．然后提出一种用来解决巨灾风险中大数据快速处理的应急分拣算法，并在汶川地震中大规模灾害的应急救援计划中进行应用．经过采用这样的应急分拣原理，就可以在面对巨灾风险大数据的复杂、繁多和零乱的重灾事件状态下，使整个应急救援方案优化，并能够有条不紊地进行救援．
本文主要研究巨災風險大數據處理的應急分類、分解、分揀算法，給齣瞭相應的算法原理和可操作的步驟．首先根據巨災風險大數據災害規模巨大的特徵，提齣瞭一種用來解決巨災風險大數據中一級事件的應急分類與二級事件及以下更低級事件的應急分解算法，併以特大地震災害作為實例進行瞭算法應用．接著定義瞭事故災難度，用來對巨災風險大數據處理過程中，對各種級彆的事故災難後果進行不同的數字標識．然後提齣一種用來解決巨災風險中大數據快速處理的應急分揀算法，併在汶川地震中大規模災害的應急救援計劃中進行應用．經過採用這樣的應急分揀原理，就可以在麵對巨災風險大數據的複雜、繁多和零亂的重災事件狀態下，使整箇應急救援方案優化，併能夠有條不紊地進行救援．
본문주요연구거재풍험대수거처리적응급분류、분해、분간산법，급출료상응적산법원리화가조작적보취．수선근거거재풍험대수거재해규모거대적특정，제출료일충용래해결거재풍험대수거중일급사건적응급분류여이급사건급이하경저급사건적응급분해산법，병이특대지진재해작위실례진행료산법응용．접착정의료사고재난도，용래대거재풍험대수거처리과정중，대각충급별적사고재난후과진행불동적수자표식．연후제출일충용래해결거재풍험중대수거쾌속처리적응급분간산법，병재문천지진중대규모재해적응급구원계화중진행응용．경과채용저양적응급분간원리，취가이재면대거재풍험대수거적복잡、번다화령란적중재사건상태하，사정개응급구원방안우화，병능구유조불문지진행구원．
This paper mainly studies the emergency algorithms on classification, decomposition and sorting when dealing with a catastrophe risk big data, and researches the corresponding algorithm principle and the operational steps. First, according to the catastrophe risk big huge disaster data, this paper proposes a method for solving a large data catastrophe risk classification and two emergency events the following lower-level events and emergency incidents decomposition algorithm, and earthquake disaster as an example of the algorithm applied. And then, it defines an accidents disaster degree. It is used for processing the catastrophe risk of large data, the various levels of disasters consequences of different digital identities. Furthermore, it proposes a method for solving catastrophe risk contingency rapid processing of large data sorting algorithms, and large-scale disasters in the earthquake emergency rescue plan for application. After adopted the principle of the emergency sorting algorithm, we can optimize the whole emergency rescue plans and the ability to conduct it orderly during in the face of catastrophe risk large complex data with many disastrous events and messy state. The emergency classification, decomposition, sorting algorithms are suitable for processing all catastrophe risk large data, and therefore the proposed algorithms can effectively solve the emergency treatments of catastrophic risk big data.
