巨灾风险大数据处理应急分类、分解、分拣算法与应用

The algorithms of emergency classification,decomposition and sorting for processing a catastrophe risk of large data and its applications

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.

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.