摘要
研究基于关系代数的非连续数据路径挖掘算法,提升网络通信中非连续数据的传输质量与利用率,改善网络通信质量。运用基于关系代数的关联规则挖掘算法,得到网络数据库内非连续数据的关联规则;以基础支持向量机为基础,结合待选支持向量预选取、全新隶属度函数设定及粒子群优化算法约简支持向量,获得改进的模糊支持向量机;以所获得的非连续数据关联规则作为其输入,完成对网络内非连续数据路径的分类挖掘。仿真结果表明,上述算法可通过对支持向量的约简,减少分类后正、负类样本的数量,有效降低挖掘用时,提升整体挖掘速度,同时保障高精度挖掘;网络应用该算法所挖掘路径实施非连续数据传输后,能够显著提升非连续数据的发送成功率并降低接收时延,改善网络对非连续数据的利用率与传输质量。
This paper studied the discontinuous data path mining algorithm based on relational algebra,improved the transmission quality and utilization rate of discontinuous data in network communication,and improved the quality of network communication.The association rules mining algorithm based on relational algebra was used to obtain the association rules of discontinuous data in the network database;Based on the basic support vector machine,combined with the pre selection of the support vector to be selected,the setting of a new membership function and the particle swarm optimization algorithm to reduce the support vector,an improved fuzzy support vector machine was obtained;With the obtained discontinuous data association rules as its input,the classification mining of discontinuous data paths in the network was completed.The simulation results show that the algorithm can reduce the number of positive and negative samples after classification by reducing the support vector,effectively reduce the mining time,improve the overall mining speed,and guarantee the high precision mining.When the path mined by this algorithm is applied to the network for discontinuous data transmission,the success rate of discontinuous data transmission can be significantly improved,the receiving delay can be reduced,and the utilization rate and transmission quality of discontinuous data can be improved.
作者
薛欢庆
张玲
范广玲
XUE Huan-qing;ZHANG Ling;FAN Guang-ling(School of Mathematical Sciences,Daqing Normal University,Daqing Heilongjiang 163712,China;College of Mathematics and Statistics,Northeast Petroleum University,Daqing Heilongjiang 163311,China)
出处
《计算机仿真》
北大核心
2022年第11期392-397,共6页
Computer Simulation
基金
黑龙江省高等教育教学改革重点委托项目(SJGZ 20210001)。
关键词
关系代数
非连续数据
路径挖掘
关联规则
支持向量机
粒子群优化
Relational algebra
Discontinuous data
Path mining
Association rules
Support vector machine
Particle swarm optimization
作者简介
薛欢庆(1970-),女(汉族),山东巨野人,硕士研究生,副教授,研究方向:计算数学。;张玲(1978-),女(汉族),黑龙江肇州人,博士,副教授,研究方向:计算数学。;范广玲(1967-),女(汉族),黑龙江呼兰人,博士研究生,副教授,研究方向:数据挖掘。
