基于神经模糊的货车车型分类技术的研究  

Study on Truck Classification Based on Neural-Fuzzy Techniques

作　　者：张青[1] 李季[1] 

机构地区：[1]中国农业大学,北京100083

出　　处：《拖拉机与农用运输车》2007年第2期3-5,共3页Tractor & Farm Transporter

摘　　要：根据目前中国高速公路车辆收费标准,提出了一种应用于货车的神经模糊分类方法。该方法通过货车几何尺寸与类型的相关性分析,得出货车几何尺寸与类型相关度很大。分类过程中采用神经模糊技术中的NEFCLASS数据分析软件,通过先确定轴数情况下再选择车长、车宽、车高参数,得出的分类精度为88.58%。This paper introduces a neural-fuzzy classification method on truck based on newly enacted uniform industry standard of vehicle classification of the toll for highway adopted and puts forward a very large correlation between vehicle type and outline geometrical size of truck according analysis between outline geometrical size and type of the truck. According the analysis the approach that using NEFCLASS date analysis software and parameter after separated the amount of the axes of the vehicle attains a very satisfying results that is 88.58%.

关 键 词：货车 车型分类 神经模糊 几何尺寸 NEFCLASS 

分 类 号：U495[交通运输工程—交通运输规划与管理]