基于Elman神经网络的交通数据融合模型

A Fusion Model of Traffic Data Based Elman Neural Network

介绍了交通数据的概念、采集方法和特性,简单概括了的特点和作用,结合现代交通数据采集手段多样化的特点和交通数据的特性,选取融合参数并提出一种基于Elman神经网络的浮动车和WSN交通检测数据融合模型。详细介绍了模型的组成、功能和基于BP神经网络交通数据融合方法进行了对比分析,并以大连中山路星海街路段为对象,通过实际检测数据和VISSM模拟数据相结合的方法进行了实验分析。

This paper gives an introduction about the concept, collection methods and characters of traffic data, briefly summarizing the characters and function of Elman neural network,and then select fusion parameter and point out A fusion model of traffic detection data for Floating cars and WSN based Elman Neural network .Later, it brings out an presentation about constitution and function of the model in detail.And in this paragraph also introduced another mathod of data fusion by BP neural network and the difference of the two neural network. It gets the analytical points through the methods of combining pragmatic data detection and VISSM data simulation based on the real detection data of the xing hai intersection at Zhong Shan road of Dalian.