Article citationsMore>>

Keogh, E. and Pazzani, M. (1998) An Enhanced Representation of Time Series Which Allows Fast and Accurate Classification, Clustering and Relevance Feedback. Proceedings of the 3rd International Conference of Knowledge Discovery and Data Mining, The Association for the Advancement of Artificial Intelligence, New York, 239-241.

has been cited by the following article:

• TITLE: Cluster Analysis of Electrical Behavior

  AUTHORS: Lin Liu

  KEYWORDS: K-Means Clustering Analysis, Principle Component Analysis, The Power System

  JOURNAL NAME: Journal of Computer and Communications, Vol.3 No.5, May 25, 2015

  ABSTRACT: In this paper, we apply clustering analysis of data mining into power system. We adapt K-means clustering algorithm to analyze customer load, analyzing similar behavior between customer of electricity, and we adapt principal component analysis to get the clustering result visible, Simulation and analysis using matlab, and this well verify cluster rationality. The conclusion of this paper can provide important basis to the peak for the power system, stable operation the power system security.