摘要
交通流预测是智能电梯群控系统的重要组成部分 ,对交通流进行预测可使群控系统跟随交通流的变化调节控制策略。将基于神经网络的时间序列预测理论应用到电梯群控系统的交通分析中 ,构造了一种交通流时间序列预测模型 ,并提出了调整预测神经网络结构以提高预测精度的方法。仿真实验表明了这种交通流智能预测方法是有效的。
Traffic flow forecasting is an important part of Elevator Group Control System (EGCS), by forecasting traffic volume, EGCS can follow the change of traffic flow and apply suitable control strategy are the way to realize the optimization of elevator assignment. This paper applies Neural Network based time serials prediction theories to EGCS's traffic analysis, and constructs a time series neural networks model, and give the method of adjusting structure of NN and improving the precision of forecasting. Simulation results show its validity.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2001年第7期103-104,F003,共3页
Systems Engineering and Electronics
基金
天津市自然科学基金资助课题 (99380 12 11)
