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Jingrong Wang

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Proceedings Article | 23 August 2023 Paper

A prediction model of urban fire with grey Markov model

Ziwen Zheng, Slam Nady, Jingrong Wang, Mingtong Zhang

Proceedings Volume 12784, 127840R (2023) https://doi.org/10.1117/12.2691815

KEYWORDS: Fire, Data modeling, Matrices, Neural networks, Systems modeling, Police, Modeling, Inspection, Error analysis, Reflection

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In recent years, urban fires have become a frequent topic of hot search, the casualties and economic losses caused by many discussions, urban fires are getting more and more attention. Forecasting the number of fires by computer is beneficial to reduce the losses caused by fires and provide assistance for arranging the deployment of fire police and making decisions as soon as possible. Based on the prognostication of fire accidents using the gray model, a Markov model is introduced to rectify the residual error in the prediction of the gray model, thereby enhancing its predictive accuracy. In this paper, the fire accident data of Beijing from 2015 to 2020 were used for modeling and verification analysis, and the future was predicted to judge the change trend. The experimental results show that the accuracy of the grey prediction model combined with Markov model is higher than that of GM(1, 1).The mean square error ratio is accurate to within 3.8 percentage points, and the optimized model can be more effectively utilized for predicting the incidence of fire accidents.

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