The Australian wildfires in 2019–2020 have brought suffering to the Australian people. It is essential to use models to help the Victorian government monitor and predict the occurrence and development of fires to the greatest extent possible under the principles of safety and economy to facilitate rapid response. Through the idea of -means algorithm and greedy algorithm, we, respectively, analyzed cities and rural areas at different altitudes and combined the altitude with the obtained clusters; the analysis from the established model shows that, for cities, cluster areas with smaller clusters with an altitude of less than 1600 meters and areas with smaller clusters with an altitude of greater than or equal to 1800 meters are covered by an EOC; for areas with larger clusters less than or equal to 600 meters above the sea level and areas with larger clusters greater than or equal to 1000 meters above the sea level, we use two EOCs for coverage; for rural areas, all areas with smaller clusters are covered by one EOC, while for areas with larger clusters where the altitude is less than or equal to 1000 meters and the altitude is greater than or equal to 1600 meters, we use two EOCs for coverage; also, obtained through greedy algorithm analysis, one EOC corresponds to 14 SSA UAVs and 8 repeater UAVs, and two EOCs correspond to 12 repeater UAVs and 26 SSA UAVs. We have a reason to believe that, through our mathematical model and the leaps in drone technology, it will have a long-term and profound impact on Australia’s wildfire control.

中文翻译：

---

基于K-Means算法的澳大利亚山火应急中心设置研究

2019-2020年的澳大利亚山火给澳大利亚人民带来了苦难。使用模型帮助维州政府在安全和经济的原则下最大可能地监测和预测火灾的发生和发展，以促进快速反应至关重要。通过这个想法——手段算法和贪心算法，我们分别分析了不同海拔的城市和农村地区，并将海拔高度与获得的聚类结合起来；对建立模型的分析表明，对于城市来说，海拔小于1600米的小集群区域和海拔大于或等于1800米的小集群区域都被EOC覆盖；对于海拔小于或等于600米的较大集群区域和海拔大于或等于1000米的较大集群区域，我们使用两个EOC进行覆盖；对于农村地区，所有集群较小的地区都由一个EOC覆盖，而对于集群较大的地区，海拔小于等于1000米，海拔大于等于1600米，我们使用两个 EOC 进行覆盖；另外，通过贪心算法分析得到，1个EOC对应14架SSA无人机和8架中继无人机，2个EOC对应12架中继无人机和26架SSA无人机。我们有理由相信，通过我们的数学模型和无人机技术的飞跃，将对澳大利亚的野火控制产生长期而深远的影响。