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Research on emergency decision-making information mining based on existing “obstacle” between geographic entities in spatial topological relations

机译:基于空间拓扑关系中地理实体之间现有“障碍”的应急决策信息挖掘研究

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Emergency decision-making mining must consider “obstacle” between the geographic entities in spatial topological relations and their intrinsic relationship, or the integrity and accuracy of the mining results would not be guaranteed. Based on the deep research above, the mechanism and law of geospatial information was explored, the traditional spatial topological relations were expanded. The number of topological relation between point, line and region was 11. By constructing the qualitative expression (ϑ: DIR9: DIR4), the topological relations were expressed qualitatively, and the spatial reasoning was realized. Meanwhile, the algorithm of decision-making information mining was studied. Combining with the abstract algebra theory, the mining algorithm was constructed. Based on the expanded topological relations above, the traditional information mining algorithms were improved. Through the analysis of emergency response decision-making information intent, this paper expands the theory of traditional information extraction methods to solve the theoretical and technical problems, which provides a support for the scientific and reasonable emergency decision-making, etc. This case study demonstrates the feasibility and effectiveness of the decision-making information mined from this study.
机译:紧急决策挖掘必须考虑空间拓扑关系中的地理实体与其固有关系之间的“障碍”,否则将无法保证挖掘结果的完整性和准确性。在以上深入研究的基础上,探索了地理空间信息的机理和规律,扩展了传统的空间拓扑关系。点,线和区域之间的拓扑关系数为11。通过构造定性表达式(ϑ:DIR 9 :DIR 4 ),定性表达拓扑关系,并实现了空间推理。同时,研究了决策信息挖掘算法。结合抽象代数理论,构造了挖掘算法。在上述扩展的拓扑关系的基础上,对传统的信息挖掘算法进行了改进。通过对应急决策信息意图的分析,扩展了传统信息提取方法的理论,解决了理论和技术问题,为科学合理的应急决策等提供了支持。从这项研究中获得的决策信息的可行性和有效性。

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