Traffic pattern recognition method for novel elevator system
新型电梯群控系统交通模式识别方法

The traffic pattern recognition is essential in elevator group control systems.Based on the varying elevator traffic flow data,a new elevator traffic flow pattern recognition method is presented.Without additional assignment,original traffic data is pretreated,and then an elevator traffic flow pattern recognition classifier based on multi-value support vector machines is built.The proposed pattern classifier can adaptively recognize the largest traffic flow floor in the building.Experimental results demonstrate that this method can recognize different traffic modes accurately and is better than the artificial neural-network method.