期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2017
卷号：95
期号：20
页码：5415
出版社：Journal of Theoretical and Applied
摘要：The Artificial Neural Network is a technique that modeled from the ways of human brain acts. The unsupervised training is a self-learning process which is performing a classification without outside teaching help. The Self-Organizing Map is an algorithm that consists process of generated neurons to organize by themselves. This paper proposes a way of analysis of the Self-Organizing Map (SOM) applied to the classification of the standard IEEE 33-bus and 69-bus distribution data. The distribution bus data were classified based on four main features: active power (MW), reactive power (MVAr), apparent power (MVA), and power factor (pf). These features are the input for SOM classification. The analysis of SOM result has shown the capability of this algorithm as a classification method in order to classify the distribution bus data.
关键词：Self-Organizing Maps (SOM); IEEE 33-bus Distribution Data; IEEE 69-bus Distribution Data
