A clustering method of Gas load based on FCM-SMOTE

¹ BEIJING GAS GROUP CO., LTO., 100035 Beijing, China
² BEIJING GAS GROUP CO., LTO., 100035 Beijing, China
³ BEIJING GAS GROUP CO., LTO., 100035 Beijing, China
⁴ BEIJING GAS GROUP CO., LTO., 100035 Beijing, China
⁵ SCHOOL OF MODERN POST (SCHOOL OF AUTOMATION), Beijing University of Posts and Telecommunications, 100876 Beijing, China

^a Xing Hao Zhao: zhxh@bupt.edu.cn

Abstract

For the design and planning of gas-fired boiler system, the load of gas-fired boiler is an important basic data. Load clustering analysis, combined with the application of data mining technology and gas boiler system, excavates the hidden load patterns in a large number of disordered and irregular loads, and classifies them, so as to solve many problems in gas boiler system. The current load clustering methods have more or less problems. The invention first carries out data PVA dimension reduction processing on the huge gas data, and then carries out cluster analysis. In the actual application of gas-fired boilers, the data objects we are faced with are usually unbalanced data sets. In order to solve the problem of sample imbalance, we use the FCM-SMOTE algorithm to oversample the clustered data to make the data set into a balanced data set.