基于多值分类SVM的电梯交通模式识别

Pattern Recognition of Elevator Traffic Mode Based on Multi-value Classification Support Vector Machine

针对电梯群控系统中的交通模式识别问题,提出一种基于多值分类支持向量机(SVM)的电梯交通模式识别方法。采用直接多值分类SVM对采集的电梯交通流数据进行分析,得到交通模式分类器,从而解决电梯交通流模式识别中多输入、多输出的非线性系统辨识问题。实验结果表明,该方法可实现全局最优且分类误差较小,能满足群控系统的要求。

Aiming at the problem of pattern recognition of traffic mode in elevator group control system,this paper proposes a pattern recognition method of elevator traffic mode based on multi-value classification Support Vector Machine（SVM）.It analyzes the collected elevator traffic flow data using the direct multi-value classification SVM.The traffic mode classifier is established and it can provide an efficient solution for the recognition of non-linear system with multiple-input and multiple-output.Experimental results show that the method can result in global optimization,small classification errors and the ability to meet group control systems.