doi: 10.7763/IJIET.2013.V3.338
The Study of Quantitative Forecasting Model on City Emergency Incidents
Nan Gao1
,
Xueming Shu2 ,
Jiting Xu1 , , ,
- 1Computer Science and Engineering Department, University of South Carolina, Columbia, SC 29205 USA
- 2Institute for Public Safety Research, Tsinghua University, Haidian District, Beijing, 100084
Abstract
Emergency incidents forecasting is quite significant to emergency response in Mega cities. In this paper, emergency incidents data were collected and data processing and analysis work were conducted. It is obvious that some rules exist when data was counted in different time spans (year and month). With discovered rules regression models were constructed and one of the current popular data mining software, Weka, was used to train and test the models. The results demonstrated that constructed linear regressed year-model and month-models fit the original data well (the MARE, mean average relative absolute error is less than 5%). The year and months' emergency incidents trend can be predicted based on this model. At the end of this article, some factors that produce model deviations were discussed from social activities perspective.
Keywords
- Cross validation
- emergency incidents
- forecasting
- linear regression
How to Cite
Nan Gao, Xueming Shu, Jiting Xu, Biao Wen, Peng Chen, and Peng Wu, "The Study of Quantitative Forecasting Model on City Emergency Incidents," International Journal of Information and Education Technology, vol. 3, no. 5, pp. 575-577, 2013. https://doi.org/10.7763/IJIET.2013.V3.338
Copyright & License
Copyright © 2013 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).