电力系统自动化2001，Vol.25Issue(2)：32-35,39,5.
用于暂态稳定评估的人工神经网络输入空间压缩方法
INPUT DIMENSION REDUCTION IN NEURAL NETWORK TRAINING FOR TRANSIENT STABILITY ASSESSMENT
摘要
Abstract
This paper proposes a rough-set-based approach for input dimension reduction in artificial neural network, which is used for power system transient stability assessment (TSA). Several discretization methods for the continuous data set are tested and evaluated. The 10-machine 39-bus New England system is used for simulation. Six out of the original 11 features are selected using rough set attribute reduction techniques. Comparison results show that the ANN classifier with the reduced input dimension is as effective as before, while the training data set compressed 45.5%.关键词
电力系统/暂态稳定评估/神经网络/粗糙集/决策表分类
信息技术与安全科学引用本文复制引用
张琦,韩祯祥,曹绍杰,顾雪平..用于暂态稳定评估的人工神经网络输入空间压缩方法[J].电力系统自动化,2001,25(2):32-35,39,5.基金项目
@@国家自然科学基金资助项目(##59777011). （##59777011）
