Abstract
With the development of information technology, the amount of data generated by people are increasing and accumulating at an unprecedented rate. For huge amounts of data and complex data structures, there are new challenges on traditional data mining algorithms. Based on the border conflict events in edgeways, this paper studies the identification and coupling relationship of key elements in the process of emergency communication to reveal the temporal and spatial regularity. The research detects abnormal patterns and spatial agglomeration by using open source intelligence information and geographic information in virtual space, and quickly identifies the key elements of social emergencies and coupling relations at all levels. This paper studies the significance of point and surface in coupling relationship of key elements and behavior decision relationship between nodes themselves and nodes in game networks, which provides theoretical basis and technical support for the follow-up experiment for cascade effect simulation and early warning system for emergencies.
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Acknowledgments
This work is supported by National Natural Science Foundation of China (Grant Nos. 61772550, 61572521, U1636114), National Cryptography Development Fund of China Under Grants No. MMJJ20170112, National Key Research and Development Program of China Under Grants No. 2017YFB0802000, the Natural Science Basic Research Plan in Shaanxi Province of china (Grant Nos. 2016JQ6037) and Guangxi Key Laboratory of Cryptography and Information Security (No. GCIS201610).
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Duan, YY., Wang, X.A., Li, F., Zhang, JD. (2019). Coupling Relationship Construction of Key Elements in Emergency Intelligence with Big Data. In: Barolli, L., Javaid, N., Ikeda, M., Takizawa, M. (eds) Complex, Intelligent, and Software Intensive Systems. CISIS 2018. Advances in Intelligent Systems and Computing, vol 772. Springer, Cham. https://doi.org/10.1007/978-3-319-93659-8_99
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DOI: https://doi.org/10.1007/978-3-319-93659-8_99
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