摘要
提出了一种基于模糊理论的有效车型识别分类方法,该方法采用基于聚类的二级评判模型,能够比较真实准确地反映实际情况,不仅大大减少了主观因素决断的影响,而且判断执行的效率较高,满足实时性要求。结果表明该方法有效提高了智能车型的识别率,同时具有很好的可扩展性。
Proposes an effective method based on fuzzy set theory to classify traffic vehicle.Such method uses two-hierarchy synthesis evaluation model based on fuzzy clustering and can truly and accurately reflect practical situations.It can not only reduce influences caused by subjective factors in a large-scale,but also be performed in a high efficiency way,meeting real-time requisition.The results of study manifest that it improves the level of recognition and meanwhile has a well expandable capability.
出处
《计算机工程与应用》
CSCD
北大核心
2005年第12期202-205,共4页
Computer Engineering and Applications
基金
国家自然科学基金项目(编号:79970025)
国家部委预研基金项目
关键词
模糊聚类分析
模糊综合评判
特征提取
车型分类
fuzzy clustering analysis,fuzzy synthesis evaluation,feature extraction,vehicle classification
