基于并行粒子群算法的最大容错瓦片挖掘算法

Zhixiang Li, Hongmei Zhang, Xiangli Zhang, Dongsheng Qi
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引用次数: 0

摘要

目前最大容错性瓦片挖掘存在以下问题:1)挖掘速度慢2)挖掘速度受容错性影响较大。为了解决这些问题,本文提出了一种基于并行粒子群算法的最大容错瓦片挖掘算法。采用粒子群算法快速准确地找到最大容错块,并结合Spark框架进一步提高了计算速度。与整数线性规划的最大容错瓦片挖掘算法相比,实验结果在速度和稳定性上都优于传统算法。将该算法应用于风力发电系统,实验结果表明,该算法对实际系统的数据集具有较好的准确性和可预测性。
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Maximum Fault Tolerant Tile Mining Algorithm Based on Parallel PSO
The current maximum fault-tolerant tile mining has the following problems: 1) the mining speed is slow 2) the mining speed is greatly affected by the tolerance. To solve these problems, a maximum fault-tolerant tile-mining algorithm based on parallel PSO is proposed in this paper. PSO algorithm is used to find the maximum fault-tolerant tile quickly and accurately, and the Spark framework is combined to further improve the calculation speed. Compared with the maximum fault-tolerant tile mining algorithm of integer linear programming, experimental results are superior to traditional algorithms in speed and stability. Then the proposed algorithm was applied to wind power generation system, and the experiment outcome shows that the algorithm is accurate and eddective for the dateset of real system.
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