山岳救援中的搜索发现概率
发布时间：2018-10-18 20:49
【摘要】：为了提高山岳救援的搜索效率,克服现有扫视宽度值适用范围受限的问题,分析传统的反立方横距函数发现概率模型的不足,构建了基于视距的线性横距函数,并以此确定发现概率模型,同时与反立方横距函数的发现概率模型进行比较。结果表明:覆盖率C=0.76时发现概率差值最大;覆盖率C≤2时平均差值为0.015,两曲线符合度较好。通过实例计算发现,由线性横距函数构建的发现概率模型的实用性较强,应用便捷,结果较为准确,可替代反立方横距函数,为制定搜索决策提供依据。
[Abstract]:In order to improve the search efficiency of mountain rescue and overcome the problem that the applicable range of the existing scan width is limited, this paper analyzes the shortcomings of the traditional anti-cubic transverse distance function discovery probability model, and constructs the linear horizontal distance function based on the line-of-sight. The discovery probability model is determined and compared with the discovery probability model of the anti-cubic transverse distance function. The results show that the probability difference is the largest when the coverage C is 0.76, the average difference of coverage C 鈮，
本文编号：2280329
[Abstract]:In order to improve the search efficiency of mountain rescue and overcome the problem that the applicable range of the existing scan width is limited, this paper analyzes the shortcomings of the traditional anti-cubic transverse distance function discovery probability model, and constructs the linear horizontal distance function based on the line-of-sight. The discovery probability model is determined and compared with the discovery probability model of the anti-cubic transverse distance function. The results show that the probability difference is the largest when the coverage C is 0.76, the average difference of coverage C 鈮，
本文编号：2280329
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