8results about How to "Guaranteed system performance" patented technology

The invention relates to the technical field of information and data processing, and discloses an intelligent recommendation method and system for a bone fracture rehabilitation training plan based on traditional Chinese medicine, and the method comprises the steps: dividing image information according to labels, and obtaining skeleton data sets with different functions; taking the first position information and the second position information as a special information set; deleting the special data set from the skeleton data set to obtain a target data set; obtaining position information of the bones to be subjected to bone fracture rehabilitation training from the target data set, and selecting matched contents such as shadowboxing, eight-section brocade or five-poultry play from a pre-stored traditional Chinese medicine rehabilitation training database; deleting related actions of the second position information from an action data set corresponding to the content; guiding the trainee to perform bone fracture rehabilitation training through the visual terminal; the system comprises a first data set construction module, a second data set construction module and a target action output module. According to the bone fracture rehabilitation training system and method, biological feature recognition and personalized, precise and systematic bone fracture rehabilitation training are achieved.

The invention relates to a hierarchical federal learning method oriented to a heterogeneous environment, and belongs to the technical field of artificial intelligence. The method comprises the following steps: constructing a hierarchical federal learning framework in a cloud edge end scene; constructing a hierarchical federated learning algorithm capable of reducing model performance loss caused by heterogeneity between nodes; constructing a virtual data set used in the edge server enhancement algorithm and a data distribution mode of the edge server; under the strict mathematical hypothesis, the boundary of the average global gradient deviation is theoretically deduced to quantify the influence of the cloud edge aggregation interval, the number of participating devices and other important factors, and the theoretical convergence boundary of the hierarchical federated learning algorithm under the influence of the heterogeneous environment is analyzed.

The application relates to the technical field of artificial intelligence, and discloses a highway side slope deformation intelligent identification and prediction system based on space-air-ground stereoscopic monitoring, which comprises a space-air-ground stereoscopic monitoring module, a data fusion processing module, an intelligent identification module, a deformation prediction module and a central control module; the space-air-ground stereoscopic monitoring module cooperatively collects side slope deformation data by using multi-source heterogeneous sensors, including space satellite remote sensing data, sky unmanned aerial vehicle aerial photography data and ground Internet of Things sensor data, realizes all-weather and multi-scale monitoring of side slope surface displacement, internal stress, crack expansion and environmental factors, guarantees the comprehensiveness and real-time performance of the monitoring data, and eliminates the limitations of a single data source; the data fusion processing module performs space-time registration, denoising and normalization processing on the multi-source monitoring data, guarantees the accuracy and reliability of real-time deformation risk diagnosis, and reduces the false alarm rate.

The application discloses an interactive form design method and system based on a language large model, and belongs to the technical field of human-computer interaction and form automatic generation. In view of the problems that a traditional form design tool is tedious to operate, highly depends on manual experience, and an existing method based on a large model has high training cost, weak interaction ability and difficulty in real-time collaboration, the following scheme is used for improvement: defining a JSON Schema specification of a form and constructing a visual form designer, integrating a language large model interaction entrance in an interface, dynamically assembling a request containing user instructions, a JSON Schema specification and existing form data according to whether the form is empty, and submitting the request to the language large model; receiving a response in a streaming manner, and real-time analyzing and progressively updating a form designer preview interface, so that a user can directly generate or modify a form through natural language instructions, and multi-round interaction and manual subsequent adjustment are supported. The method is mainly used for reducing a form design threshold, improving design efficiency and intelligent collaboration level.

The present application belongs to the technical field of aircraft state estimation. The present application provides an aircraft state estimation method combining multi-model interactive filtering and DNN. The disclosed embodiment trains the LSTM network model according to the collected aircraft trajectory set, and the LSTM-KF filter uses the nonlinear function formed by the LSTM network model to replace the original state transfer matrix for state prediction update, and connects the LSTM-KF filter as a filter module to the interactive multi-model filtering framework. This method has interactions between multiple different models, and can adapt well to the complex motion mode of the aircraft, even when the aircraft motion mode jumps, it can still adapt well, and at the same time integrates the results of the deep neural network filter to improve the upper limit of the aircraft state estimation accuracy.

The invention relates to the technical field of tobacco baking, and provides a baking process based on the quality of fresh tobacco leaves of Xiangyan No.7. The baking process comprises the following steps: S1, carrying out near infrared spectrum scanning on harvested fresh tobacco leaves to obtain near infrared spectrum data of each tobacco leaf; s2, dividing the near infrared spectrum data into a training set and a test set; s3, taking the near infrared spectrum data of each tobacco leaf in the training set as an input vector, inputting the input vector into a self-organizing neural network model for clustering, and dividing the tobacco leaves into three subsets; s4, aiming at the three divided subsets, baking process parameters are optimized according to a three-section baking process, and the three-section baking process comprises a yellowing period, a color fixing period and a stem drying period; and S5, performing near infrared spectrum scanning on newly harvested tobacco leaves, classifying the newly harvested tobacco leaves through the self-organizing neural network model, determining subsets to which the newly harvested tobacco leaves belong, and according to the baking process curves corresponding to the subsets, sequentially executing the baking processes of a yellowing period, a color fixing period and a stem drying period.

This application provides an application installation method, apparatus, device, and medium based on compilation optimization, relating to the field of computer technology. The method includes: in response to an installation operation on a target application, obtaining an application package corresponding to the target application; extracting baseline configuration files for various scenarios included in the application package; installing the target application based on the application package, and compiling hotspot code corresponding to a first configuration file that meets the compilation requirements during installation from the baseline configuration files for each scenario; and, when it is determined that the electronic device is in an idle state, compiling hotspot code corresponding to a second configuration file (excluding the first configuration file) from the baseline configuration files for each scenario, thereby completing the installation of the target application. This method aims to save resources, improve performance, and enhance the user experience.

The invention discloses a driving assistance system reliability test method, and the main design concept of the method lies in that: through employing a mode of building a system test, signal interaction and work cooperation among almost all actual parts in a system needing to be complete are realized, and an overall real vehicle network communication ecological idea is employed. The simulation equipment rack is used for simulating a real vehicle communication environment except for the system, information interaction between the tested function system and all systems in the external vehicle is ensured, a shielding mode is not adopted, and therefore it is better ensured that the test result is more scientific and effective. The system-level verification scheme with repeatability and comprehensive simulation of working conditions, provided by the invention, is true and effective, meets different working conditions and scenes, is more in line with actual use characteristics, provides support for effective verification and quality assurance of a driving assistance system, and is of great significance to improvement of safety and comfort quality of a whole vehicle.