基于混合蛙跳算法的K-mediods聚类挖掘与并行优化  

K-mediods Cluster Mining and Parallel Optimization Based on Shuffled Frog Leaping Algorithm

作　　者：魏霖静[1] 宁璐璐 郭斌 侯振兴[4] 甘诗润 WEI Lin-jing;NING Lu-lu;GUO Bin;HOU Zhen-xing;GAN Shi-run(School of Information Science&Technology,Gansu Agriculture University,Lanzhou 730070,China;School of Light Industry Science&Engineering,Shaanxi University of Science and Technology,Xi’an 710021,China;College of Computer and Information,Hohai University,Nanjing 210094,China;School of Information Management,Nanjing University,Nanjing 210093,China)

机构地区：[1]甘肃农业大学信息科学技术学院,兰州730070 [2]陕西科技大学轻工科学与工程学院,西安710021 [3]河海大学计算机与信息学院,南京210094 [4]南京大学信息管理学院,南京210093

出　　处：《计算机科学》2020年第10期126-129,共4页Computer Science

基　　金：甘肃农业大学学科建设专项项目(GAU-XKJS-2018-257);甘肃农业大学青年导师扶持基金项目(GAU-QDFC-2018-13);兰州市科技计划项目(2019-1-31);甘肃省教育厅创新基金(2020B-122);国家自然科学基金(61063028,31560378)。

摘　　要：为了降低K-mediods聚类算法的误差并提高并行优化的性能,将混合蛙跳算法运用于聚类和并行优化过程。在K-mediods聚类过程中,将K-mediods与聚类簇思想相结合,对各个聚类簇进行混合蛙跳算法优化,从而提高了大规模数据样本聚类的效率。针对多个聚类执行节点并行完成大规模样本K-mediods聚类时,混合蛙跳算法有效提高了加速比。实验证明,相比于普通的K-mediods聚类,基于混合蛙跳算法的K-mediods聚类优势明显,且处理大规模样本的加速比性能更优。In order to reduce the error of K-mediods clustering algorithm and improve the performance of parallel optimization,the shuffled frog leaping algorithm is applied to the clustering and parallel optimization process.In the K-mediods clustering process,K-mediods is combined with the clustering cluster idea to optimize the shuffled frog leaping algorithm for each cluster cluster,which improves the efficiency of large-scale data sample clustering,especially for multiple clusters.When the class execution nodes complete the large-scale sample K-mediods clustering in parallel,the shuffled frog leaping algorithm effectively improves the speedup ratio.It has been proved by experiments that the K-mediods clustering based on the shuffled frog leaping algorithm has obvious clustering advantages compared with the common K-mediods clustering,and the acceleration ratio performance of processing large-scale samples is better.

关 键 词：混合蛙跳算法 K-mediods聚类 并行优化 聚类簇 加速比 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]