The invention relates to a vehicle quality determination method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: periodically acquiring multiple groups of target characteristic values of a vehicle longitudinal dynamic model within a preset time period; updating a plurality of model parameters of the preset number of initial deep neural network models for three times based on the plurality of groups of target feature values; and determining the whole vehicle mass of the target vehicle based on the deep neural network model updated for the third time. According to the method provided by the invention, the occupation of on-chip resources can be reduced, and the convergence duration in the training process of the deep neural network model can be effectively shortened.
本申请涉及一种整车质量确定方法、装置、计算机设备、计算机可读存储介质和计算机程序产品。所述方法包括:在预设时间段内周期性地获取车辆纵向动力学模型的多组目标特征值;基于多组目标特征值,对预设数量个初始深度神经网络模型的多个模型参数进行三次更新;基于第三次更新后的深度神经网络模型确定目标车辆的整车质量。本申请提供的方法,能够减少对片上资源的占用,并且能够有效缩短深度神经网络模型训练过程中的收敛时长。
Whole vehicle quality determination method and device, computer equipment, readable storage medium and program product
整车质量确定方法、装置、计算机设备、可读存储介质和程序产品
2024-12-10
Patent
Electronic Resource
Chinese
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