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Academic Journal of Computing & Information Science, 2022, 5(9); doi: 10.25236/AJCIS.2022.050908.

Fire Rescue Model Based on Time Series Analysis


Hu Han

Corresponding Author:
Hu Han

School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu, Anhui, China


In this paper, we establish relevant models for the problems in fire rescue and solve them. Using the ARIMA model to establish a prediction model for the number of fire rescue calls, and predict the number of fire rescue calls in each month in 2021. According to the characteristics of fire incidents, we divide fire incidents into 7 levels, and use the method of cluster analysis to analyze the spatial correlation of various incident densities in this area, and give the most relevant incident categories in different regions. Grey correlation analysis was used to analyze the relationship between the density of various events and population density in the area. And on this basis, based on the minimum distance between the new fire station and other areas, the Floyd algorithm is used to solve the shortest distance between each area and other areas, and the location where the new fire station should be built is analyzed.


Time series analysis, K-means cluster analysis, Grey relational analysis, Floyd algorithm

Cite This Paper

Hu Han. Fire Rescue Model Based on Time Series Analysis. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 9: 45-51. https://doi.org/10.25236/AJCIS.2022.050908.


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