基于非参数估计与随机模拟的不确定数据流相似性度量方法  

An Uncertain Data Stream Similarity Measurement Method Based on Nonparametric Estimation and Stochastic Simulation

作　　者：迟荣华 黄少滨[1] 李熔盛 CHI Rong-hua;HUANG Shao-bin;LI Rong-sheng(College of Computer Science and Technology/Harbin Engineering University,Harbin 150001,China)

机构地区：[1]哈尔滨工程大学计算机科学与技术学院,黑龙江哈尔滨150001

出　　处：《山东农业大学学报（自然科学版）》2017年第4期521-524,共4页Journal of Shandong Agricultural University：Natural Science Edition

摘　　要：针对不确定数据流对象难于度量相似性的问题,本文提出一种非参数估计与随机模拟相结合的方法。本方法利用非参数估计对不确定数据流对象建模,然后利用随机模拟计算对象间的误差相似性,通过相对距离与绝对距离判断相似度。仿真实验验证了本方法不仅可以准确地度量不确定对象间的相似性,而且在对象规模较大的情况下,依然可以获得较快速和稳定的计算结果。To solve the problem that the current uncertain data stream is difficult to measure the similarity,this paperproposes a method combining non-parametric estimation with stochastic simulation.The method used the non-parametricestimation to model the uncertain data stream objects,and then used stochastic simulation to calculate the error similaritybetween objects,judged the similarity by relative distance and absolute distance.Simulation experiment verified this methodcan not only measure the similarity between the uncertain objects accurately,but also can obtain fast and stable results whenthe object scale is large.

关 键 词：不确定数据流 非参数估计 随机模拟 相似性 

分 类 号：TP274.2[自动化与计算机技术—检测技术与自动化装置]