The Frontiers of Society, Science and Technology, 2024, 6(11); doi: 10.25236/FSST.2024.061102.
Shu Fan
School of Public Security Information Technology and Intelligence, Criminal Investigation Police University of China, Shenyang, China
Facing the challenges of the big data era, traditional emergency intelligence generation methods are no longer able to meet timeliness and quality requirements. This study proposes a new emergency intelligence process that draws on the core ideas of complex network theory. Comparative analysis shows that the core concepts of the emergency intelligence process and the complex network empirical analysis process are highly consistent. Based on this theoretical basis, an emergency intelligence process based on complex networks is constructed. This process makes the intelligence generation process more systematic and significantly enhance its explanatory power.
emergency intelligence process; complex network; intelligence production
Shu Fan. Research on Emergency Intelligence Process Based on Complex Networks. The Frontiers of Society, Science and Technology (2024), Vol. 6, Issue 11: 9-14. https://doi.org/10.25236/FSST.2024.061102.
[1] Qian C. Hierarchical holographic modeling of network ideology risks: strategies for governance in the big data era [J]. International Journal of Cognitive Informatics and Natural Intelligence, 2024, 18(1): 1-16.
[2] Costa L D F, Rodrigues F A, Travieso G and Boas P R V. Characterization of Complex Networks: A Survey of Measurements [J]. Advances in Physics, 2007, 56(1): 167-242.
[3] Lobsang T, Zhen F, Zhang S Q, Xi G L and Yang Y. Methodological Framework for Understanding Urban People Flow from a Complex Network Perspective[J]. Journal of Urban Planning and Development, 2021, 147(3): 25-37.
[4] Chen X J, Jia S B and Xiang Y. A Review: Knowledge Reasoning over Knowledge Graph [J]. Expert Systems with Applications, 2020, 141(1): 1-21.
[5] Xia M R, Wang J H and He Y. BrainNet Viewer: A Network Visualization Tool for Human Brain Connectomics[J]. Plos One, 2013, 8(7): 1-15.