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Небесная энциклопедия

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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Мониторинг СМИ

Мониторинг СМИ и социальных сетей. Сканирование интернета, новостных сайтов, специализированных контентных площадок на базе мессенджеров. Гибкие настройки фильтров и первоначальных источников.

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Применить Всего найдено 3. Отображено 3.
14-07-2023 дата публикации

Driver and conductor risk identification method and device

Номер: CN116434200A
Автор: SONG JIANHUA, ZHANG YAN, WANG SHIHUI, WANG YESHUAI, HE PENG, MA CHUANXIANG, HUANG CHEN, LI YAMIN, LYU SHUNYING, YANG CHAO
Принадлежит:

The invention relates to a driver and conductor risk identification method and device, and the method comprises the steps: inputting collected real-time pressure data into an emotion identification model, and determining a current emotion state; if the current emotional state is an emotional state of a preset type, continuously obtaining multiple groups of pressure data in a preset time period, inputting the pressure data into an emotion recognition model, and obtaining a plurality of corresponding target emotional states; according to the multiple target emotional states, determining an early warning counting result in a preset time period, and if the early warning counting result reaches a preset counting threshold, generating a risk early warning result; wherein the emotion recognition model is trained in the following mode: inputting sample pressure data with emotion label information into an initial recognition model for training until the recognition success rate of the trained recognition ...

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Номер записи: 1
25-03-2015 дата публикации

Vehicle driving path prediction method and system

Номер: CN104464344A
Автор: MA CHUANXIANG, WANG SHIHUI, YU XIAO, ZENG CHENG, CHEN HAO, ZHANG, LYU SHUNYING, SONG JIANHUA, WU SIYAO
Принадлежит:

The invention provides a vehicle driving path prediction method and system. The method includes the steps that a minimum internal storage is determined on the basis of a Hadoop platform, the largest length of a path is scanned, and an original path sequence database is evenly divided into n disjoint sub-path sequence databases; the original path sequence database and the n sub-path sequence databases are respectively uploaded to an HDFS; the n sub-path sequence databases are dispatched to different Map nodes by a master control node, each Map node executes an improved GSP algorithm, the sub-path sequence databases stored in a Map node internal storage are scanned according to a preset minimum supporting degree X, a local path sequence mode is worked out, and Reduce nodes are merged and processed so that an overall candidate sequence mode can be obtained; the original path sequence database is scanned again so that an overall path sequence mode can be obtained; the overall path sequence ...

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Номер записи: 2
09-06-2023 дата публикации

Public area personnel perception method and device

Номер: CN116245704A
Автор: ZHANG YAN, WANG SHIHUI, SONG JIANHUA, WANG YESHUAI, HE PENG, MA CHUANXIANG, HUANG CHEN, LI YAMIN, LYU SHUNYING, YANG CHAO
Принадлежит:

The invention relates to a public area personnel perception method and device, and the method comprises the steps: collecting the pressure data of a pressure sensor matrix according to a preset time interval, and obtaining the pressure data of each sampling moment in a preset time period; according to the pressure data of each preset position in the preset time period, screening from each preset position to obtain at least one target position meeting a preset condition; at each sampling moment, according to the pressure data corresponding to the at least one target position, determining target sensing data of the public area at the sampling moment; determining target weight data corresponding to a preset time period based on the target sensing data corresponding to each sampling moment; and determining a personnel gathering perception result according to the target weight data and a preset weight threshold value. The method is high in sensitivity and recognition speed, and compared with ...

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Номер записи: 3