基于模糊GMDH网络的交通流量预测模型  

Model of Traffic Volume Forecasting Based on Fuzzy GMDH Network

作　　者：陈洪[1,2] 陈森发[1] 

机构地区：[1]东南大学系统工程研究所,江苏南京210096 [2]南京工程学院数学研究所,江苏南京211167

出　　处：《南京理工大学学报》2010年第1期46-50,共5页Journal of Nanjing University of Science and Technology

基　　金：教育部博士点基金(20060286005);江苏省高校自然科学基金(07KJD580085)

摘　　要：针对传统数据处理组合方法(Group method of data handling,GMDH)网络建模用最小二乘法辨识参数会导致模型预测效果不理想的问题,将模糊推理模型引入GMDH网络,以取代传统GMDH网络的部分描述(即完全二元二次多项式),提出了一种基于模糊GMDH网络的交通流量预测模型。计算机仿真结果表明,该模型预测平均相对误差仅为2.31%,小于传统GMDH网络模型预测平均相对误差3.35%,说明了该模型是有效的。In view of the undesirable forecasting results from the conventional group method of data handling （GMDH） network modeling that uses the least square method to identify coefficients, this paper introduces a fuzzy reasoning model into the GMDH network to take the place of partial descriptions of the traditional GMDH network, i.e. the integral binary quadratic polynomial forms. Based on the GMDH network, this paper proposes a model of traffic volume forecasting based on a fuzzy GMDH network. Simulation results show that the average relative error of the new model prediction is only 2.31%, and it is less than 3.35% which is the average relative error of prediction of the traditional GMDH network. The new model is proved effective.

关 键 词：数据处理组合方法 网络 模糊 交通流量 预测 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] U491.14[自动化与计算机技术—控制科学与工程]