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19 July 2024 A shortest path algorithm based on individual characteristics for mine water disaster rescue
Ruiqi Liu, Jiyuan Ma, Xiao Fang, Xuyang Song, Wei Chen, Gang Lin, Ling Fan, Cong Cao, Wensheng Yu
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Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 131815R (2024) https://doi.org/10.1117/12.3031007
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China
Abstract
The occurrence of mine water disasters has brought huge losses. At present, the strategies and algorithms for mine water disaster rescue are mostly based on the Dijkstra algorithm, and usually do not consider the impact of individual differences among trapped individuals. In response to the impact of individual differences on rescue methods, this article analyzes the impact of water level and water flow velocity on human stability, as well as the prediction of the physical condition of trapped individuals. A method for calculating the risk coefficient is proposed, and a mine water disaster rescue model based on human characteristics is established. This article simulates a personalized rescue algorithm for Dijkstra underground optimal path rescue based on personal characteristics using Java programming language in the Eclipse development environment. The experimental results indicate that in mine water disaster rescue, selecting the shortest rescue path based on individual characteristics can fully utilize the capacity of the tunnel system and develop more accurate rescue plans for specific individuals.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Ruiqi Liu, Jiyuan Ma, Xiao Fang, Xuyang Song, Wei Chen, Gang Lin, Ling Fan, Cong Cao, and Wensheng Yu "A shortest path algorithm based on individual characteristics for mine water disaster rescue", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 131815R (19 July 2024); https://doi.org/10.1117/12.3031007
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KEYWORDS
Mining
Mathematical modeling
Floods
Algorithms
Safety
Mathematical optimization
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