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Космические корабли и станции, автоматические КА и методы их проектирования, бортовые комплексы управления, системы и средства жизнеобеспечения, особенности технологии производства ракетно-космических систем

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Применить Всего найдено 2. Отображено 2.
22-08-2023 дата публикации

Vehicle monitoring data processing method

Номер: CN116628618A
Автор: YOU JIAXUN, CHENG SHENGLONG, ZHAO ZHENG, WANG BIN, LYU SHUOYING, XUE NANNAN, WANG WENBIN, WANG HUAJUN, LU YANGYANG, ZHENG YUNSHUANG, WANG XIAOJIE, HU XUELAN, SONG RUISHENG, YANG JIE, WANG SHIBO
Принадлежит:

The invention provides a vehicle monitoring data processing method, and belongs to the technical field of monitoring data cleaning, and the method comprises the following steps: obtaining monitoring data of a commercial vehicle at each collection moment, the types of the monitoring data being various; extracting different types of target monitoring data sets with a coupling relationship from the monitoring data; for the target monitoring data of the specified type, constructing a filtering function according to the distance between the target monitoring data of other types; wherein the other types are types except the specified type in the target monitoring data set; filtering the target monitoring data of the specified type by adopting the filtering function; according to the method, the relationship between data of mutually associated parameter types can be comprehensively considered, relevance filtering is adopted, the actual running condition of the vehicle is reflected, real monitoring ...

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Номер записи: 1
25-08-2023 дата публикации

Commercial vehicle fuel consumption prediction method, electronic equipment and storage medium

Номер: CN116644865A
Автор: GU HONGJIAN, WANG BIN, ZHAO ZHENG, XUE NANNAN, SONG RUISHENG, TIAN CHENG, PANG JINXI, YANG YING, LU YANGYANG, REN JIE, CHENG SHENGLONG, WU ZEZHAN
Принадлежит:

The invention relates to the field of artificial intelligence, and discloses a commercial vehicle fuel consumption prediction method, electronic equipment and a storage medium, the method comprises the following steps: obtaining current vehicle data of a commercial vehicle, and determining initial dynamic data and initial static data from the current vehicle data according to dynamic factors and static factors; processing the initial dynamic data based on a pre-trained attention mechanism fusing the relative position and the distance to obtain a to-be-fused dynamic feature; based on a factorization machine algorithm, processing the initial static data to obtain static features to be fused; according to the to-be-fused dynamic features and the to-be-fused static features, performing adaptive feature fusion to obtain target features; and inputting the target feature into a pre-trained multi-layer perceptron to obtain fuel consumption prediction data. The method can achieve the effect of improving ...

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Номер записи: 2