Dynamic Production Scheduling Method and Apparatus Based on Deep Reinforcement Learning, and Electronic Device

    公开(公告)号:US20220179689A1

    公开(公告)日:2022-06-09

    申请号:US17524335

    申请日:2021-11-11

    Abstract: The embodiments of the present invention provide a dynamic production scheduling method, apparatus and electronic device based on deep reinforcement learning, which relate to the technical field of Industrial Internet of Things, and can reduce the overall processing time of jobs on the basis of not exceeding the processing capacity of production device. The embodiments of the present invention includes: acquiring static characteristics, dynamic characteristics of each of jobs and system dynamic characteristics, inputting the static characteristics, dynamic characteristics of each of jobs to be scheduled and system dynamic characteristics into a scheduling model to obtain a job execution sequence or batch execution sequence of the jobs in each production stage, wherein, the static characteristics of the job include an amount of tasks and time required for completion, the dynamic characteristics of the job include reception moment, and the system dynamic characteristics include a remaining amount of tasks that can be performed by the device in each production stage. The scheduling model is a model obtained after training a first actor network based on static characteristics and dynamic characteristics of a sample job, system dynamic characteristics, and a first critic network.

    METHOD AND DEVICE FOR DETERMINING SCORING MODELS OF A THREE-DIMENSIONAL ANIMATION SCENE FRAME

    公开(公告)号:US20170109918A1

    公开(公告)日:2017-04-20

    申请号:US14993612

    申请日:2016-01-12

    Abstract: The embodiments of the present invention provide a method and a device for determining scoring models of a three-dimensional animation scene frame, the method comprising: obtaining a dataset of three-dimensional animation scene frames; obtaining a predetermined stereoscopic effect standard score and a predetermined visual comfort standard score corresponding to each three-dimensional animation scene frame; obtaining the disparity map of each three-dimensional animation scene frame, extracting disparity statistic features of each three-dimensional animation scene frame based on its disparity map, and combining the disparity statistic features into one feature vector; and, determining the stereoscopic effect scoring model and the visual comfort scoring model for a three-dimensional animation scene frame respectively based on the feature vector of each three-dimensional animation scene frame in conjunction with the corresponding stereoscopic effect standard score and visual comfort standard score, in order to achieve the automatic scoring of three-dimensional animation scene frames and reduce the influence of subjective factors from the producers on the scoring. The workload is also reduced and the efficiency is improved.

    Method, apparatus for cross-protocol opportunistic routing, electronic device and storage medium

    公开(公告)号:US11683398B2

    公开(公告)日:2023-06-20

    申请号:US17505175

    申请日:2021-10-19

    Abstract: The embodiments of the present invention provide a method, apparatus for cross-protocol opportunistic routing, an electronic device, and a storage medium, the method includes: when there is a first data packet in a low-power wireless network, simulating the first data packet to generate a second data packet including to-be-transmitted data in the first data packet; obtaining identification information of a destination node in the first data packet, and selecting a low-power node with the lowest delay to the destination node in the low-power wireless network, except the first low-power node, as a forwarding low-power node based on the identification information of the destination node; sending the generated second data packet to the forwarding low-power node, so that the forwarding low-power node forwards the to-be-transmitted data to the destination node. By using high-power nodes, when there is a data packet in the low-power node, the data packet can be sent in time without being transmitted in a reserved idle channel, thereby reducing the transmission delay of the data packet from the source node to the destination node in the low-power wireless network.

    Method and system for determining parameters of an off-axis virtual camera

    公开(公告)号:US09754379B2

    公开(公告)日:2017-09-05

    申请号:US15012442

    申请日:2016-02-01

    CPC classification number: H04N13/296 G06T7/13 G06T7/60 H04N13/275

    Abstract: A method and a system for determining parameters of an off-axis virtual camera provided by embodiments of present invention can extract a scene depth map for each video frame from a depth buffer, determine the minimum value of edge depth values of the scene depth map as the closest scene edge depth of each video frame, determine the depth of a first object as the depth of an object of interest of each video frame, use the smaller value between the closest scene edge depth and the depth of an object of interest as the zero-parallax value and obtain a zero-parallax value sequence constituted by the zero-parallax value of each video frame. The present invention realizes automatic determination of the zero parallax of each video frame rather than manual setting thereof, and thus the determination will not be affected by factors such as lack of experience, and the amount of work for an technician is also reduced. Meanwhile, the present invention makes the zero parallax as close as possible to an object of interest without incurring the window occlusion problem, which can improve the stereo perception as much as possible while ensuring the comfortability, and can ensure the using effect of the determined zero parallax.

    Dynamic production scheduling method and apparatus based on deep reinforcement learning, and electronic device

    公开(公告)号:US12153954B2

    公开(公告)日:2024-11-26

    申请号:US17524335

    申请日:2021-11-11

    Abstract: The embodiments of the present invention provide a dynamic production scheduling method, apparatus and electronic device based on deep reinforcement learning, which relate to the technical field of Industrial Internet of Things, and can reduce the overall processing time of jobs on the basis of not exceeding the processing capacity of production device. The embodiments of the present invention includes: acquiring static characteristics, dynamic characteristics of each of jobs and system dynamic characteristics, inputting the static characteristics, dynamic characteristics of each of jobs to be scheduled and system dynamic characteristics into a scheduling model to obtain a job execution sequence or batch execution sequence of the jobs in each production stage, wherein, the static characteristics of the job include an amount of tasks and time required for completion, the dynamic characteristics of the job include reception moment, and the system dynamic characteristics include a remaining amount of tasks that can be performed by the device in each production stage. The scheduling model is a model obtained after training a first actor network based on static characteristics and dynamic characteristics of a sample job, system dynamic characteristics, and a first critic network.

    Acoustic sensing-based text input method

    公开(公告)号:US11322142B2

    公开(公告)日:2022-05-03

    申请号:US16675816

    申请日:2019-11-06

    Abstract: Embodiments of the present application provide an acoustic sensing-based text input method, comprising: obtaining audio information corresponding to text to be input; dividing the audio information to obtain an audio segment for each letter to be recognized in the text to be input; sending to the server, a type of the text to be input, the audio segments for letters to be recognized, and arrangement of the audio segment for the letter to be recognized in the audio information; receiving input result returned by the server, and displaying, based on the input result, text information corresponding to the text to be input on the display screen of the mobile terminal. The method allows effective text input without relying on a display screen.

    Method, Apparatus for Cross-Protocol Opportunistic Routing, Electronic Device and Storage Medium

    公开(公告)号:US20220124179A1

    公开(公告)日:2022-04-21

    申请号:US17505175

    申请日:2021-10-19

    Abstract: The embodiments of the present invention provide a method, apparatus for cross-protocol opportunistic routing, an electronic device, and a storage medium, the method includes: when there is a first data packet in a low-power wireless network, simulating the first data packet to generate a second data packet including to-be-transmitted data in the first data packet; obtaining identification information of a destination node in the first data packet, and selecting a low-power node with the lowest delay to the destination node in the low-power wireless network, except the first low-power node, as a forwarding low-power node based on the identification information of the destination node; sending the generated second data packet to the forwarding low-power node, so that the forwarding low-power node forwards the to-be-transmitted data to the destination node. By using high-power nodes, when there is a data packet in the low-power node, the data packet can be sent in time without being transmitted in a reserved idle channel, thereby reducing the transmission delay of the data packet from the source node to the destination node in the low-power wireless network.

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