A Study on Process Data Compression Method by Clustering Method
Yoonsik Kim, Mo Kyung Joo, Yoon En Sup · Journal of the Korean Institute of Gas · 2000
Data compression and retrieval method are investigated for the effective utilization of measured process data. In this paper, a new data compression method, Clustering Compression(CC), which is based on the k-means clustering algorithm and piecewise linear approximation method is suggested. Case studies on industrial data set showed the superior performance of clustering based techniques compared to other conventional methods and showed that CC could handle the compression of multi-dimensional data.