Machine Learning Algorithm Study on Refrigerator Parameter Analysis

被引：1
|
作者：
Xu, Wenjin [1 ,2 ]
Feng, Yuan [1 ]
Zhou, Di [3 ]
机构：
[1] Ocean Univ China, Qingdao 266101, Shandong, Peoples R China
[2] Qingdao Univ Sci & Technol, Qingdao 266069, Shandong, Peoples R China
[3] 91049 Army PLA, Qingdao, Shandong, Peoples R China
来源：
2019 2ND INTERNATIONAL CONFERENCE ON MECHANICAL, ELECTRONIC AND ENGINEERING TECHNOLOGY (MEET 2019) | 2019年
关键词：
Machine Learning; K-means; Support Vector Machine; Information Analysis;
D O I：
10.23977/meet.2019.93707
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, we systematically study the two kinds of data mining algorithm and software simulation process in refrigerator data analysis. This paper mainly introduces the related content of machine learning and data mining algorithm, including the concept, background of machine learning, model and the relevant methods. Then we implement two kinds of data mining algorithms: K - means algorithm and support vector machine (SVM) algorithm in refrigerator parameter analysis. Finally, we discuss the result of real-time data mining algorithm, using simulation software to realize the analysis of the data instance.
引用
收藏
页码：40 / 47
页数：8
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