随机森林在群控电梯交通模式识别中的应用

Elevator Group Control Traffic Pattern Recognition Based on Random Forest

运用随机森林算法设计一种电梯模式识别系统。通过采集当前电梯运行中的有效数据,组成训练数据,用随机森林法建立模式识别模型,基于该模型设计模式识别系统。将电梯的运行参数带入基于随机森林建立的模式识别模型,得出群控电梯的交通模式,实验结果与预期相同。理论分析与实验结果表明,把随机森林算法运用到电梯交通模式识别中,既可以有效地识别出电梯当前的交通模式,又可以提高分析速度。该算法适用于辨识各种群控电梯交通模式,具有灵活性。

It utilizes the random forest algorithm to design an elevator pattern recognition system.By collecting the valid data in the current elevator operation to form the training data,it establishes a pattern recognition model by using the Random Forest Algorithm.Then it brings the operating parameters of the elevator into the pattern recognition model which is built on the basis of the Random Forest Algorithm to obtain the traffic mode of the group control elevator and get the conclusion that the simulation result is the same with expected.Theoretical analysis and simulation results show that applying the Random Forest Algorithm to the traffic pattern recognition of elevators can not only effectively identify the current traffic pattern of the elevator,but also can improve the speed of analysis.The algorithm can be applied to the identification of the traffic pattern of a variety of group control elevators and it owns the merit of flexibility.