%0 Journal Article
%T 基于关联及Kmeans算法对泵数据的分析<br>Analysis of Pump Data Based on Association and Kmeans Algorithm
%A 刘子熠
%A 张喆
%A 高天
%A 武强
%J Hans Journal of Data Mining
%P 129-135
%@ 2163-1468
%D 2020
%I Hans Publishing
%R 10.12677/HJDM.2020.102013
%X 针对泵企业在泵出厂前的性能检测以及运行不稳定等问题，本文应用多元线性回归、Apriori算法分析有关泵的特征之间的相关性，去除冗余属性，然后在去除了冗余属性的特征基础上应用Kmeans算法进行聚类分析，找出了出水压力与流量间的关系，两根线的电压间的关系，三相电流和出水压力间的关系等结论。<br />
Aiming at the performance test and unstable operation of the pump before leaving the factory, this paper uses multiple linear regression and Apriori algorithm to analyze the correlation between the characteristics of the pump, and removes the redundant attributes, and then uses the kmeans al-gorithm to carry out cluster analysis on the basis of removing the redundant attributes, to find out the relationship between the effluent pressure and the flow rate, and the relationship between the voltage of the two lines as well as the relationship between three-phase current and effluent pres-sure.
%K 多元回归，Kmeans，聚类，关联分析<br>Multiple Regression
%K Kmeans
%K Clustering
%K Correlation Analysis
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=35064