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USE OF NEURAL NETWORKS IN ROAD RECOGNITION BY VIBRATION DATA

机译:振动数据在道路识别中的神经网络应用

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This paper deals with road recognition by the use of neural networks on vibration signals. In particular, an accelerometer sensor is used and it acquires the vibrations transmitted in the contact between the tyres and the ground. Twelve different types of road have been tested at different speed of the car. Based on these data a neural network has been proposed to correlate a set of suitable characteristics of the vibration signal with the type of road. The effectiveness of the resulting neural network has been proved on a control set of data. Moreover the paper reports a sensitivity analysis of the neural network in order to minimize the number of inputs needed and to make it rugged.
机译:本文通过使用神经网络对振动信号进行道路识别。特别地,使用加速度传感器,并且该加速度传感器获取在轮胎与地面之间的接触中传递的振动。已经在不同速度的汽车上测试了十二种不同类型的道路。基于这些数据,已经提出了一种神经网络,以将振动信号的一组合适的特性与道路类型相关联。结果神经网络的有效性已在一组控制数据上得到证明。此外,该论文还报告了神经网络的敏感性分析,以最大程度地减少所需输入的数量并使其坚固耐用。

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