7results about How to "Improve build accuracy" patented technology

Embodiments of the present disclosure disclose a process page display method and device, electronic equipment and a computer readable medium. A specific embodiment of the method comprises: in response to receiving a process page rendering request, obtaining code information and a set of business processing criteria information; generating initial full business process information; verifying the execution relationship between the initial full business process information, obtaining full business process information; rendering the full business process information and rendering and displaying it on the process page; in response to selecting selection information, generating a matching business batch as a first business batch; and displaying the corresponding business process processing tree on the process page. This embodiment can accurately render the corresponding business process information on the process page after receiving the business data related to the business process generation uploaded to the process page, and can set various page filtering operations for the business process information, greatly improving the rendering efficiency of the business process.

The application provides a point cloud encoding method and device based on a prediction tree, equipment and a storage medium. The method comprises the following steps: obtaining a target point cloud, the target point cloud comprising N points; constructing a main prediction tree based on part of the main nodes in the N points; inserting the adjacent points of the main nodes in the remaining points into the main nodes to obtain a target prediction tree of the target point cloud for each main node in the main prediction tree; and encoding the target point cloud based on the target prediction tree. That is, the application takes the main nodes as the center, optimizes the connection relationship between the local points, and prevents the connection of points far away from each other. The target prediction tree obtained in this way realizes the optimal ordering of the local points, improves the construction accuracy of the target prediction tree. When prediction is performed based on the accurately constructed target prediction tree, the prediction accuracy of the target point cloud can be improved, and the encoding efficiency of the target point cloud is further improved.

The application discloses a kind of dam deformation prediction method, equipment, storage medium and product, the prediction method includes preprocessing to dam monitoring data;The environmental data after pretreatment is extracted to depth feature, and environment characteristic is obtained;The reservoir water level after pretreatment and environment characteristic are carried out cluster analysis, and according to the time domain division of time factor and dam survey point displacement according to cluster analysis result, obtain the cluster division result of different time periods;According to each cluster division result, respectively construct sample data set;Each sample data set is used to train and test Transformer-LSTM model respectively, and the dam deformation prediction model of each time period is obtained;Obtain the data to be predicted, and the dam deformation prediction model corresponding to the time period of the data to be predicted is used to predict the prediction data, and the dam deformation prediction result is obtained.The dam deformation prediction precision of the application is improved.

The present application discloses a device fault analysis method and related device, electronic equipment and storage medium, wherein the device fault analysis method comprises: obtaining target text about fault state of a target device; processing the target text based on a first large model to obtain a first fault analysis text, and processing the target text based on a second large model to obtain a second fault analysis text; wherein the first large model is obtained based on an initial large model through parameter fine-tuning, and the second large model is generated by retrieval enhancement; comparing a first confidence of the first fault analysis text with a second confidence of the second fault analysis text to obtain a first comparison result; and obtaining a target fault analysis text of the target device based on the first comparison result, the first fault analysis text and the second fault analysis text. The above scheme can improve the accuracy of the target fault analysis text while improving the robustness of the device fault analysis.

This application provides a method, apparatus, equipment, and medium for generating a secondary safety measures sheet for a technical upgrade substation. The method includes acquiring secondary equipment information and main wiring diagram information of the technical upgrade substation; performing correlation analysis on the secondary equipment information and main wiring diagram information of the technical upgrade substation based on preset substation information to determine the equipment correlation information corresponding to the technical upgrade of the substation; the preset substation circuit model includes preset secondary equipment information within the substation, preset main wiring diagram information, and preset correlation circuit information between each equipment bay; and generating a secondary safety measures sheet for the technical upgrade substation based on the equipment correlation information, thereby improving the accuracy of the secondary safety measures sheet generation.

This application discloses a method, storage medium, and program product for determining the semantics of a problem, relating to the field of artificial intelligence technology. The method includes: acquiring user questions that do not match within a preset time period to obtain a problem to be maintained, and acquiring a target standard question corresponding to the problem to be maintained; acquiring tags matching the problem to be maintained from a tag library to obtain a candidate tag set, and constructing a first prompt word based on a generation instruction, the problem to be maintained, and the candidate tag set. The generation instruction is used to mask a preset vocabulary according to the candidate tag set and generate at least two semantic expressions for the problem to be maintained; inputting the first prompt word into a target expression generation model to generate a candidate semantic expression set corresponding to the problem to be maintained; determining the target semantic expression from the candidate semantic expression set, and adding the target standard question and the target semantic expression to a problem matching library. This improves the efficiency and accuracy of determining the semantics of a problem and enhances the accuracy of the business service platform's responses.