摘要
基于神经网络-模糊推理(N N-FR)的数据融合方法——自适应神经网络-模糊推理信息融合系统(A N N-FRIFS),对交通中同一检测面上的多种检测器采集的数据进行融合。首先简单介绍了A N N-FR IFS,然后分析了AN FIS置信度判别器的设计,并给出了A N N-FRIFS算法,最后结合仿真算例,验证了该方法能以较高精度对同一检测面上的多检测器进行数据融合。
Based on Neural Network and Fuzzy Reasoning （NN-FR） , the adaptive NN-FR Information Fusion System （ANN-FRIFS） is used to fuse the data which are collected by multi-detector in the same traffic detecting section. ANN-FRIFS is first introduced, then the design of ANFIS confidence estimator is analyzed and the algorithm of ANN-FRIFS is given. Finally, an example is illustrated, which indicates that the method given in this paper can fuse the data which are collected by multi-detector in the same detecting section with high precision.
出处
《公路交通科技》
CAS
CSCD
北大核心
2006年第7期120-124,共5页
Journal of Highway and Transportation Research and Development
