The invention provides a vehicle mass determination method and device, equipment, a medium and a program product, and relates to the field of electronic automobiles, the method comprises the steps that multiple sets of sampling time periods of a vehicle are acquired, and each set of sampling time periods comprises a first sampling time period about an estimated non-gear-shifting period of the vehicle and a second sampling time period about an estimated gear-shifting period of the vehicle; inputting the vehicle data corresponding to each group of sampling time periods into a pre-trained deep learning model to obtain score classification results of a non-gear-shifting period and a gear-shifting period corresponding to each group of sampling time periods, and determining the non-gear-shifting period and the gear-shifting period of the vehicle according to the score classification results; wherein the deep learning model is a model which is obtained based on historical vehicle data training and is used for carrying out score classification on a non-gear-shifting period and a gear-shifting period of the vehicle; the mass of the vehicle is calculated and determined based on the vehicle data for the non-shift period and the shift period. According to the method, the non-gear-shifting period and the gear-shifting period of the vehicle are accurately identified, so that the calculation precision of the vehicle quality can be effectively improved.
本申请提供一种车辆质量的确定方法、装置、设备、介质及程序产品,涉及电子汽车领域,方法包括:获取车辆的多组采样时间段,每组采样时间段包括关于车辆的预估非换挡期的第一采样时间段和预估换挡期的第二采样时间段;分别将每组采样时间段对应的车辆数据输入至预训练的深度学习模型中,得到每组采样时间段对应的非换挡期和换挡期的得分分类结果,并根据得分分类结果确定车辆的非换挡期和换挡期;其中,深度学习模型是基于历史车辆数据训练得到并用于对车辆的非换挡期和换挡期进行得分分类的模型;基于非换挡期和换挡期的车辆数据,计算确定车辆的质量。本申请通过准确识别车辆的非换挡期和换挡期,可以有效提高车辆质量的计算精度。
Vehicle mass determination method and device, equipment, medium and program product
车辆质量的确定方法、装置、设备、介质及程序产品
2024-11-15
Patent
Electronic Resource
Chinese
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