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Mining Algorithm of Regular Route of Target of Sea Battlefield based on Neighborhood ε-dist

机译:基于邻域邻域ε-dist的海运目标规律途径挖掘算法

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Mining on regular route of target is an important research subject of analysis on sea battlefield situations. Aiming at the problem that there is enormous target data in sea battlefield target, which is difficult to obtain target whole-process track data, and so rules of route may only exist in part of area, this paper proposes one mining algorithm on regular route of target in sea battlefield based on neighborhood ε-dist. This algorithm firstly performs pre-processing on massive sea and air target track data, reduces the complete target track into sequence of several straight-line track segments by using the simplified method based on straight-line, then brings out a kind of track segment similarity distance SSD according to mutual relationship between pairs of straight-line track segments, and based on this distance, neighborhood ε-dist is defined. By using the density clustering algorithm based on neighborhood ε-dist, track segments is divided into several non-intersecting clusters. For each cluster, core track segment will be extracted, which will be combined to form mining results on regular route of target. Experiments show that method proposed in this paper is better than current algorithm in the aspect of mining accuracy of rules in part of route, which can be applied to mining and analysis applications of rules in target route under environment of target data in sea battlefield.
机译:挖掘定期目标路线是海运地区分析的重要研究主题。针对海运地区目标中存在巨大目标数据的问题,这很难获得目标全过程轨道数据,因此路线规则可能只存在于面积的一部分中,提出了一种在常规路线上的一个采矿算法基于邻域ε-dist的海运地区的目标。该算法首先在大量海洋和空气目标轨道数据上进行预处理,通过使用基于直线的简化方法将完整的目标轨道降低到几个直线轨道段的序列中,然后带出一种轨道段相似度距离SSD根据双直线轨道段的相互关系,并基于该距离,定义了邻域ε-dist。通过使用基于邻域ε-dist的密度聚类算法,轨道段被分成几个非交叉簇。对于每个群集,将提取核心轨道段,将组合以在规则的目标路径上形成挖掘结果。实验表明,本文提出的方法比在一部分路线中采矿准确性方面的算法优于当前算法,这可以应用于海运环境下目标数据环境下的规则的采矿和分析应用。

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