兵工自动化2026，Vol.45Issue(5)：24-27,36,5.DOI:10.7690/bgzdh.2026.05.006
基于并行计算的混合数据多约束挖掘算法仿真
Simulation of Multi-constraint Mining Algorithm for Hybrid Data Based on Parallel Computing
摘要
Abstract
In order to improve the mining efficiency of target data in a large number of mixed data,a multi-constraint mining algorithm for mixed data based on parallel computing is proposed.The wavelet threshold method is used to denoise the mixed data.A distance parallel algorithm based on the matrix multiplication function in Cublas library is proposed to obtain the distance between the mixed data.Positive and negative association constraints are extended to the denoised mixed data,and the mixed data are clustered based on the constraints and the distance between the data,and the similar data mining is completed according to the clustering results.The experimental results show that the method has good data processing effect and high data mining performance.关键词
并行计算/混合数据挖掘/多约束/小波阈值Key words
parallel computing/hybrid data mining/multi-constraint/wavelet thresholding分类
信息技术与安全科学引用本文复制引用
叶舟,李晶..基于并行计算的混合数据多约束挖掘算法仿真[J].兵工自动化,2026,45(5):24-27,36,5.基金项目
浙江省高等教育"十三五"第二批教学改革研究项目(jg20190301) （jg20190301）
