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Prediction model of fire rescue times based on BP neural network

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DOI: 10.23977/jeis.2022.070103 | Downloads: 12 | Views: 458

Author(s)

Pengcheng Lin 1, Xu Huang 1, Jiajin Shi 2

Affiliation(s)

1 School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, 210044, China
2 School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, Jiangsu, 210044, China

Corresponding Author

Pengcheng Lin

ABSTRACT

Based on the fire rescue data of a place from 2016 to 2019, this paper first establishes the BP neural network algorithm, constructs the prediction model of fire rescue times in months, and then solves it with MATLAB software to obtain the prediction value of alarm times from January to December 2021. Finally, the accuracy of the prediction model is proved by verifying the number of police calls in 2020, and the stability of the model is strong according to the BP neural network training chart.

KEYWORDS

Prediction model, BP neural network, Fire rescue

CITE THIS PAPER

Pengcheng Lin, Xu Huang, Jiajin Shi, Prediction model of fire rescue times based on BP neural network. Journal of Electronics and Information Science (2022) Vol. 7: 25-28. DOI: http://dx.doi.org/10.23977/jeis.2022.070103.

REFERENCES

[1] Liu Tianshu Improved research and application of BP neural network [D] Northeast Agricultural University, 2011
[2] Chen Weiming Research on curve fitting principle and its application [D] Changsha University of technology, 2018
[3] Wen Liang, Li Zhenbo, Chen Jiapin, Zhang Dawei Neural network blood pressure measurement algorithm based on Gaussian fitting [J] Sensors and Microsystems, 2014,33 (04): 132-134 + 138
[4] He Xiaoqun Applied regression analysis: R language version [M] Beijing Electronic Industry Press, 2017.157

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