基于SVM的电梯群控系统交通流模式识别

Pattern Recognition of Traffic Flows in Elevator Group Control Systems Based on SVM

针对电梯群控调度中的交通流模式识别问题,提出了一种基于多值分类支持向量机的电梯交通流模式识别方法.文中介绍了电梯交通流模式识别的设计流程,并建立了相应的电梯交通流模式识别器.结果表明,基于支持向量机的交通流模式识别方法能够较准确地辨识出各种交通流模式.通过对比试验,证明了该算法的识别准确率优于人工神经网络算法,体现出较好的泛化能力,具有一定的实用价值.

Aiming at the pattern recognition of traffic flows in elevator group control systems, a method based on the multi-value classification SVM (Support Vector Machine) is put forward. Moreover, the design procedure of the pattern recognition is presented and the corresponding pattern classifier is established. The results demonstrate that, by using the proposed method, different traffic flow modes can be recognized accurately. Furthermore, it is proved by comparison experiments that the proposed method possesses powerful generalization ability and is of greater re-cognition veracity than the methods based on the neural networks.