Strategy for Fighting Wildfires Using Mean-Shift Algorithm
DOI: 10.23977/acss.2021.050108 | Downloads: 2 | Views: 116
Wenbo Zhang 1
1 School of Electrical and Electronic Engineering, Harbin University of Science and Technology, Harbin, Heilongjiang, 150000
Corresponding AuthorWenbo Zhang
To deal with the wildfires in Victoria, we need to arrange the drones reasonably. Taking into account capability, safety, economy and topography, we use Mean-Shift algorithm to determinate the optimal numbers and mix of drones and predict the situation of extreme wildfires in the future. Finally, we determine the optimal number and combination of drones after optimization. According to the size, frequency and locations of wildfires in Victoria in 2019, we use logistic model to estimate the general location of the wildfires. And we use Mean Shift algorithm to find the Optimal number, mix and locations of drones. The result is we need 95 SSA drones, 122 repeater drones and 122 drones with two functions, and the total cost is $3,390,000.
KEYWORDSMean-Shift algorithm, logistic model, general location
CITE THIS PAPER
Wenbo Zhang. Strategy for Fighting Wildfires Using Mean-Shift Algorithm. Advances in Computer, Signals and Systems (2021) 5: 55-59. DOI: http://dx.doi.org/10.23977/acss.2021.050108
 Wang Mingyu, Shu Lifu, Tian Xiao. A Method for Predicting the Daily Occurrence Probability of Forest Wildfires: China, CN201410057152.5 [P]. 2014-06-25.
 Wu Dehui. Dynamic exponential smoothing prediction method and its application [J]. Journal of Systems &Management, 2008, 17(002): 151-155.
 Zhang Wenzheng, Zhang Chuanlin, Fu Wenchao. Wireless Sensor Deployment Based on Probability Coverage Model [J]. Journal of Hainan University (Natural Science Edition), 2010, 28(003): 248-251.