Optimization on Fire Station Location Selection for Fire Emergency Vehicles Using K-means Algorithm
- DOI
- 10.2991/icammce-18.2018.71How to use a DOI?
- Keywords
- Fire Station Planning, K-means, Shortest Path
- Abstract
Fire accident happens frequently with high density of population and large scale of production in cities and it will directly or indirectly cause incalculable loss. This paper evaluates the existing city fire fighting plan with historical fire alert call-out data, using the Baidu Map API to get the fire rescue path length, and then the K-means algorithm and its improved version are adopted to obtain a reasonable fire station layout according to the old ignition position data. This paper uses Baidu map API to get the shortest time, and uses K-means algorithm to screen potential fire station location, and reduces the amount of calculation. The data analysis and simulation experiment are carried out in this paper. The fire data sets in Suzhou were screened and useful data were obtained. The visualization of data is displayed on the map, and some conclusions of fire planning are obtained by intuitionistic method. The location of the fire station determined by various methods is compared with the experimental results, and the location of the fire is verified by the location of the alarm in the following month, which verifies the conclusion.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yunqian Wang PY - 2018/05 DA - 2018/05 TI - Optimization on Fire Station Location Selection for Fire Emergency Vehicles Using K-means Algorithm BT - Proceedings of the 2018 3rd International Conference on Advances in Materials, Mechatronics and Civil Engineering (ICAMMCE 2018) PB - Atlantis Press SP - 323 EP - 333 SN - 2352-5401 UR - https://doi.org/10.2991/icammce-18.2018.71 DO - 10.2991/icammce-18.2018.71 ID - Wang2018/05 ER -