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SSA Drones and Radio Repeater Drones

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DOI: 10.23977/jeis.2021.61003 | Downloads: 40 | Views: 1033

Author(s)

Longjie Zhao 1

Affiliation(s)

1 International College of Xiamen University, Xiamen, Fujian 361102

Corresponding Author

Longjie Zhao

ABSTRACT

After analyzing the background and requirements of fighting wildfires, we decide to set two models, linear programming model and grey prediction model.We start the analysis strictly from the actual situation. Since the number of drones depends on the distance between the EOC and the fire points, we creatively transform the problem of the optimal number of drones into the evaluation problem of EOC site selection. We use the sum of the distances between the EOC and various ignition points as the objective function to establish a linear programming model. Then we summarized the fire situation into three typical periods according to the actual situation, comprehensively considering the characteristics of fire incidents, the number and location of EOC, to balance ability, safety and economy. Through the immune optimization algorithm (Immune Algorithm), the problem of best address is solved, and then the number of drones required is calculated, and the best solution for the Victoria fire incident is analyzed. We not only give the number of SSAs and UAVs carrying repeaters required in various situations, but also give an accurate and optimal distribution of UAV positions through a large number of computer simulations. This shows our determination and efforts to balance economy and safety.

KEYWORDS

Drone, Immune Algorithm, Grey Prediction, Linear Programming

CITE THIS PAPER

Longjie Zhao, SSA Drones and Radio Repeater Drones. Journal of Electronics and Information Science (2021) 6: 21-26. DOI: http://dx.doi.org/10.23977/jeis.2021.61003

REFERENCES

[1] Wikipedia: 2019–20 Australian bushfire season. 2021.2.5. https://en.wikipedia.org/wiki/2019%E2%80%9320_ Australian_bushfire_season
[2] Wang Yingjie, Ding Mingtao, Zhang Minghui. Application of gray GM (1,1) model in the prediction of debris flow activity trend in Wenchuan County [J]. Geological Hazards and Environmental Protection, 2020, 31(01): 23-29.
[3] Li Zhibin. Forest fire disaster prediction in Changting County based on grey system theory [J]. Subtropical Soil and Water Conservation, 2016, 28(02): 26-29.
[4] Wikipedia:https://en.wikipedia.org/wiki/Bushfires_in_Australia
[5] Wikipedia: https://en.wikipedia.org/wiki/Climate_change_in_Australia#Pre-instrumental_climate_change
[6] Goverment:https://www.kerncountyfire.org/en/operations/divisions/office-of-emergency-services/operations-center. html#: ~:text=The%20cost%20of%20the%20EOC, voice%20data%20equipment%2C%20and%20furniture.
[7] http://forex.hexun.com/rmbhl/#zkRate

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