Refined Analysis of User Load Based on Weighted Fuzzy Clustering
Authors
J. Fan, X.L. Gao, X. Chen, K. Shi, P. Xu, H. Ye
Corresponding Author
J. Fan
Available Online October 2015.
- DOI
- 10.2991/icitmi-15.2015.22How to use a DOI?
- Keywords
- Refined Analysis; Weighted Fuzzy Clustering; Load Classification Dividing; Clustering Efficiency Estimating
- Abstract
As the development of intelligent power system, much importance and requirement have been attached to the load data analysis. In view of the current rough classification of load data, propose a weighted fuzzy clustering algorithm to detail the load classification dividing, which adds a weight distribution process to balance the different influence of various factors. In addition, Two group of experiments are set to verify the efficiency of this method. The experiment results show that the algorithm is effective to accurately cluster the load data and supportive to the fine analysis of load data.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - J. Fan AU - X.L. Gao AU - X. Chen AU - K. Shi AU - P. Xu AU - H. Ye PY - 2015/10 DA - 2015/10 TI - Refined Analysis of User Load Based on Weighted Fuzzy Clustering BT - Proceedings of the 4th International Conference on Information Technology and Management Innovation PB - Atlantis Press SP - 116 EP - 122 SN - 2352-538X UR - https://doi.org/10.2991/icitmi-15.2015.22 DO - 10.2991/icitmi-15.2015.22 ID - Fan2015/10 ER -