5results about How to "Improve decoupling ability" patented technology

The invention relates to a load prediction method TSR-MAEN based on decomposition representation and an attention encoder network. Firstly, the algorithm provides a trend-seasonal decomposition representation method based on comparative learning so as to enhance the decoupling performance of a model on a trend component and a seasonal component of a load sequence and the representation capability of decomposition characteristics. Secondly, in order to deeply mine and decompose time sequence information contained in a feature hidden space and dependency between features, the algorithm proposes a mixed attention encoder network; through segmented embedding, a trend-season dynamic projection mixed self-attention mechanism and a multi-head mixed output mechanism, trend and season multi-dimensional features after load sequence decomposition are effectively utilized to express and enhance the long-range dependence information extraction capability of the model. Experiments show that the TSR-MAEN algorithm provided by the invention has excellent performance in an electrical load prediction task of oil and gas development, and the prediction error is reduced by 8.51% compared with that of an optimal baseline algorithm.

This invention provides a force sensor comprising an annular housing, a top cover and a base respectively fixed to one end of the housing, a loading platform fixed to the top cover near the base and spaced apart from the housing and the base, at least three force-measuring beam assemblies spaced apart from each other around the periphery of the loading platform, and a first sensor device and a second sensor device disposed on each force-measuring beam assembly. Each force-measuring beam assembly includes a horizontal force-measuring beam fixed to the periphery of the loading platform and a vertical force-measuring beam fixed to the loading platform near the base. The horizontal and vertical force-measuring beams in each force-measuring beam assembly are perpendicular to each other and located in the same plane. All force-measuring beam assemblies are rotationally symmetrically distributed. The force sensor of this invention can improve its decoupling effect and simplify data processing during measurement.

The application provides a program sequence recommendation method and system based on group interest multi-level decoupling, and belongs to the technical field of personalized recommendation. The method comprises the following steps: a group sequence encoder is used to encode a group interaction sequence processed by an embedding layer to obtain a group representation; a group-level interest decoupling module is used to decouple the interest representations of different members from the group representation; a group variational autoencoder in a member-level interest decoupling module is used to further decouple the interest representations of different members decoupled by the group-level interest decoupling module to obtain decoupled representations of different members and a group consensus representation; the decoupled representations of different members and the group consensus representation are used for next item prediction to obtain candidate item scores of the group at the next moment, and the group is recommended. By using the application, the problem of poor IPTV program recommendation accuracy and robustness of the existing family group can be solved.

This invention discloses an indoor data acquisition and positioning method, positioning system, and storage medium based on a neural network algorithm. It employs a multi-terminal collaborative architecture to achieve a closed-loop positioning process for small-scale indoor scenes. The system uploads indoor planar images via a front-end device and performs scale calibration to establish a mapping relationship between pixel coordinates and physical space. In acquisition mode, it acquires multi-source signals in real time and expands the effective sample. After back-end data processing and storage, the algorithm extracts signal features through a neural network, performs adaptive weight allocation and feature fusion, and trains to generate a fingerprint database model. In positioning mode, it performs signal matching and coordinate calculation based on this model, and finally, the positioning results are visualized and displayed on the front end. This invention requires no dedicated acquisition equipment or base station deployment, and has the advantages of high positioning accuracy, low deployment cost, convenient maintenance, and user-friendly operation, making it suitable for various small-scale indoor positioning needs.

The invention relates to a vehicle which comprises a vehicle frame, a power assembly and a suspension device, the suspension device comprises a bracket and a suspension assembly, and the bracket comprises a supporting plate; the two connecting plates are connected to the two ends of the supporting plate respectively, extend upwards and are connected with a frame respectively; the lower end of the suspension assembly is installed on the upper side of the supporting plate. The power assembly comprises a first installation point and two second installation points, the two second installation points are located on the left side and the right side of the power assembly, the first installation point is located on the bottom wall of the power assembly, the front portion of the power assembly is fixed to the vehicle frame through the two second installation points, and the rear portion of the power assembly is fixed to the upper end of the suspension assembly through the first installation point. The suspension assembly is connected to the first mounting point, so that the elastic center of the suspension assembly is closer to the torque shaft, and the decoupling effect is improved. The bracket can solve the problem that no frame used for being connected with the suspension assembly exists below the bottom wall of the power assembly, the suspension assembly is installed on the bracket, and the problem can be solved by connecting the bracket to the frame.