Abnormal State Detection of OLTC Based on Improved Fuzzy C-means Clustering
Author:
Affiliation:
1. School of Automation and Electrical Engineering, Lanzhou Jiaotong University,Lanzhou,China,730070
2. School of New Energy and Power Engineering, Lanzhou Jiaotong University,Lanzhou,China,730070
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Energy Engineering and Power Technology,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/7873788/10093776/10093778.pdf?arnumber=10093778
Reference33 articles.
1. The Bivariate Empirical Mode Decomposition and Its Contribution to Grinding Chatter Detection
2. Setting Parameters of the Analytic Wavelet Transforms for Estimating Electric Power System Damping Parameters
3. Vibration-Based Signal Analysis for Shearer Cutting Status Recognition Based on Local Mean Decomposition and Fuzzy C-Means Clustering
4. Hierarchical K-means Method for Clustering Large-Scale Advanced Metering Infrastructure Data
5. A New Hybrid Algorithm Based on Grey Wolf Optimization and Crow Search Algorithm for Unconstrained Function Optimization and Feature Selection
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