灰色神经网络在汽车振动预测中的应用

Zhendong Zhao, R. Yin
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引用次数: 0

摘要

针对灰色系统方法和神经网络的理论特点,提出了一种将灰色预测模型与神经网络相结合的灰色神经网络预测方法,以提高车辆振动预测的精度。为了验证所提出的模型,对皮卡在不同行驶速度下的几个测点的振动数据进行了实验测试和理论预测。结果表明,将所提出的灰色神经网络预测方法应用于车辆振动数据计算是可行的,有效地提高了预测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Grey Neural Network in Vehicle Vibration Prediction
Considering the theoretical characteristics of grey system method and neural network, a grey neural network prediction method was proposed by combining the grey prediction model and the neural network in order to improve the accuracy of vehicle vibration prediction. On the purpose of verifying the proposed model, the vibration data of several measuring points under different traveling speed of a pick-up truck were both tested in an experimental way and predicted in a theoretical way. The results show that it is feasible to apply the proposed grey neural network prediction method to calculate the vehicle vibration data, which improves the prediction accuracy effectively.
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