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机构地区:[1]中国人民解放军71702部队
出 处:《计算机与现代化》2012年第1期30-33,63,共5页Computer and Modernization
摘 要:弹药的补给线是作战部队的生命线,主动、精确、迅速地实施弹药配送保障已成为战斗力的重要增长点,现代战争中对弹药配送的时间最优路线选择和到达时间的准确快速预测是至关重要的。通过分析传统的弹药配送方法,借助卫星图像处理技术,建立弹药配送路线的车流量预测算法和应用策略模型。通过对弹药配送的可行路线上的车流量进行预测,选择预测的车流量最少的一条路线为最优路线,车流量的速度作为弹药配送车辆的速度来预测弹药配送到达时间。为了提高车流量预测算法的可靠性和精确性,采用统计数据挖掘对算法参数优化,进而借助并行计算技术来降低算法的时间复杂度,实现对弹药配送的时间最优路线选择和到达时间的可靠、精确、快速的预测。Ammunition supply is the lifeblood of combat troops, active, accurate and rapid implementation of ammunition delivery has become an important growth point in modem warfare, fast and accurate driving route choice and time prediction of ammunition delivery are crucial. Through analyzing the traditional methods of ammunition delivery, using satellite images processing technology, the article establishes the driving route choice and time prediction algorithms of ammunition delivery and application policy model. The traffic flow of the route is the least, it is the best. The speed of traffic flow is used as the speed of delivery vehicles to predict arrival time of the ammunition delivery. In order to improve the reliability and accuracy of traffic flow prediction algorithms, statistical data mining is used to optimize the algorithm parameters, and thus to reduce the algorithms time complexity by use of parallel computing, to achieve optimal route selection of ammunition delivery and reliable, accurate and fast prediction of arrival time.
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