Computer Science Department, Universitat de València, Av. de la Universitat s/n, 46100 Burjassot, Spain.
I.U. Matemática Pura y Aplicada, Universitat Politècnica de València, Camino de Vera s/n, 46022 València, Spain.
Sensors (Basel). 2021 Jan 25;21(3):797. doi: 10.3390/s21030797.
Forest fires are undesirable situations with tremendous impacts on wildlife and people's lives. Reaching them quickly is essential to slowing down their expansion and putting them out in an effective manner. This work proposes an optimized distribution of fire stations in the province of Valencia (Spain) to minimize the impacts of forest fires. Using historical data about fires in the Valencia province, together with the location information about existing fire stations and municipalities, two different clustering techniques have been applied. Floyd-Warshall dynamic programming algorithm has been used to estimate the average times to reach fires among municipalities and fire stations in order to quantify the impacts of station relocation. The minimization was done approximately through -means clustering. The outcomes with different numbers of clusters determined a predicted tradeoff between reducing the time and the cost of more stations. The results show that the proposed relocation of fire stations generally ensures faster arrival to the municipalities compared to the current disposition of fire stations. In addition, deployment costs associated with station relocation are also of paramount importance, so this factor was also taken into account in the proposed approach.
森林火灾是对野生动物和人类生活产生巨大影响的不良情况。快速到达火灾现场对于减缓火势蔓延并有效地扑灭火灾至关重要。本工作提出了一种优化的瓦伦西亚省(西班牙)消防站分布方案,以最小化森林火灾的影响。使用关于瓦伦西亚省火灾的历史数据,以及现有消防站和自治市的位置信息,应用了两种不同的聚类技术。弗洛依德-沃肖尔动态规划算法用于估计自治市和消防站之间到达火灾的平均时间,以量化消防站重新安置的影响。通过 -means 聚类进行了近似最小化。不同聚类数目的结果确定了减少时间和更多消防站成本之间的预测权衡。结果表明,与当前消防站的配置相比,所提出的消防站重新安置通常确保更快到达自治市。此外,与消防站重新部署相关的部署成本也至关重要,因此在提出的方法中也考虑了这一因素。