汽车运行状态识别方法研究(二)——基于模糊神经网络的识别方法

Research on Vehicle Driving Situation Identification(Part Ⅱ)——Based on Fuzzy-neural Network

采用汽车运行状态特征参数的最优子集建立了一个基于模糊神经网络的汽车运行状态识别模型。对北京、上海、广州、武汉的主干道和快速路运行工况进行了识别,计算结果为:除对北京市主干道运行工况的识别准确度为82.67%外,对其余运行工况的识别准确度都为100%;对北京市主干道和快速路汽车实际运行车速的识别准确度为89.08%。

By using the best subset of the vehicle driving fication model was created herein, which was based on the fuzzy-neural network. Identifying vehicle driving cycle on the urban way and highway of the Beijing, Shanghai, Guangzhou and Wuhan,the re- suits are： except the accuracy of Beijing urban way is as 82.67 %, the accuracy of other vehicle driving cycles is as 100 % ; and the accuracy of Beiiing urban way and highway on-road driving situation is as 89. 08%.