37results about How to "Automate the build" patented technology

The invention discloses an automatic software construction method, a server and a storage medium. The method includes the steps of obtaining a source file from a source code library through the server, wherein the source file includes a to-be-processed source code and a preset deployment script; according to the to-be-processed source code, generating a plurality of program packages; according tothe preset deployment script, deploying each program package to achieve automatic software construction. Each program package is deployed through the preset deployment script, a set of flowing operation can be performed without depending on the external working environment, errors caused by manual operations are avoided, the efficiency of developing software can be effectively improved, the development cycle is shortened, the development cost is saved, and the user experience is improved.

The invention relates to a construction method for a Chinese semantic knowledge base, in particular to a machine translation-based construction method for a Chinese semantic knowledge base.The problems that Chinese semantic knowledge bases are insufficient and the labor cost and the time cost are high in the prior art are solved, and the performance of semantic knowledge base translation based on cross-language mapping is improved.The method comprises the steps that 1, a source language end corpus annotated with the entity is obtained; 2, the subject distribution of the entity is obtained through calculation according to a subject model; 3, the translation probability of the entity in the source language end semantic knowledge base is extracted from a phrase translation table according to a source language end entity word list and marked as a P (tj|si); 4, an entity translation model based on source language end semantic knowledge base graph structure information is built.The construction method is applied in the field of construction of Chinese semantic knowledge bases.

The invention provides a simulation scene three-dimensional road automatic construction method and device, and the method comprises the steps: obtaining high-precision map data for preprocessing, and creating a data element model related to a traffic scene in a three-dimensional engine; and importing the preprocessed high-precision map data into a three-dimensional engine, and constructing three-dimensional traffic scene data based on a data element model. According to the method, linear road sections, curved road sections and intersection roads in the road data are distinguished, adaptive modeling is performed, a road element model with a real visual effect is automatically constructed, meanwhile, the vertex complexity of a scene is reduced, and the rendering efficiency is improved. Compared with a traditional method that modeling personnel need to carry out manual modeling through three-dimensional software in virtual scene making, the method achieves automatic scene construction, simplifies the complexity of a scene model through a self-adaption mode, achieves rapid traffic network scene construction and high-efficiency rendering operation speed, and is suitable for large-scale popularization and application. And large-scale automatic driving simulation can be realized by combining the traffic flow and an external sensor.

The invention provides a mirror image construction method, a server, a client, a storage medium and a mirror image construction system, and the method is applied to the server and comprises the steps:receiving a to-be-constructed application file and mirror image construction information sent by the client; analyzing the mirror image construction information to generate a mirror image descriptionfile; and constructing a target application mirror image based on the to-be-constructed application file and the mirror image description file. Thus, the server can analyze the mirror image construction information, uniformly generate the mirror image description file and automatically construct the target application mirror image according to the mirror image description file and the to-be-constructed application file, so that the fragmentation process during construction of the target application mirror image is reduced, automatic construction of the application mirror image is achieved, and meanwhile, the application mirror image standardization and correctness are improved.

The embodiment of the invention belongs to the field of artificial intelligence and relates to a road network topological structure construction method. The method comprises a step of obtaining traffic flow data of each checkpoint of a road network in a preset time period, a step of taking any one checkpoint as a reference checkpoint and comparing the traffic flow data of the reference checkpointwith the traffic flow data of other checkpoints to obtain a candidate upstream checkpoint group and a candidate downstream checkpoint group of each reference checkpoint, a step of determining an upstream checkpoint of the reference checkpoint according to the candidate upstream checkpoint group, a step of determining a downstream checkpoint of the reference checkpoint according to the candidate downstream checkpoint group, and a step of constructing the road network topological structure according to the reference checkpoints and upstream checkpoints and downstream checkpoints corresponding tothe reference checkpoints and displaying the road network topological structure at the interactive interface. The invention further provides a device for constructing the road network topological structure, computer equipment and a storage medium. According to the invention, the automatic construction of the road network topological structure can be realized.

The invention relates to the technical field of computers, in particular to a component construction method and device, a storage medium and an electronic device. The method comprises: establishing acomponent definition database, and the component definition database comprising the name of each component and main parameters and user-defined parameters of each component; responding to the component construction instruction, and obtaining the name of the to-be-constructed component; obtaining main parameters and user-defined parameters of the to-be-constructed component from the component definition database according to the name of the to-be-constructed component; and constructing the to-be-constructed component according to the main parameters and the user-defined parameters of the to-be-constructed component. The construction efficiency of the assembly is improved, and the construction cost of the assembly is reduced.

The embodiment of the invention discloses an interface document management method, device, server and storage medium. Wherein, the method includes: subscribing to the distributed service center for the registered system service; receiving the address information of the system service fed back by the distributed service center; in response to the interface document construction instruction, based on the address information of the system service, calling The first interface function associated with the system service acquires corresponding interface information, and constructs an interface document according to the acquired interface information. The technical solution provided by the embodiment of the present invention can ensure the consistency of the actual interface and the interface document, and realize the isolation of the interface document between various system services.

The present disclosure provides a data warehouse information processing method, the data warehouse includes a plurality of associatively stored history tables, the method includes: obtaining at leastone history query statement, the history query statement is used for querying related data of a plurality of history tables in the associatively stored history tables; the history query statement is used for querying related data of the history tables in the associatively stored history tables. Determining a plurality of history tables corresponding to the at least one history query statement; Generating a target table based on a particular one of the plurality of history tables, the target table including relevant data in the particular history table.

The invention discloses a pneumatic tailoring optimization design method for a flexible inflatable wing structure, and belongs to the field of aircrafts. The implementation method comprises the following steps of: aiming at a flexible inflatable wing structure, optimizing the oblique sweep angle of an air beam on the premise of considering the inflatable internal pressure and the thickness of a membrane material, and selecting the maximum lift-drag ratio of a pneumatic subject and the minimum wrinkle area of a structural subject as optimization targets by taking the allowable stress of the membrane material as a constraint condition; the aerodynamic / structure multidisciplinary strong coupling effect of the flexible inflatable wing is considered, and the aeroelastic characteristic of the flexible inflatable wing structure is improved from the bottom layer design level of changing system rigidity distribution. In the optimization process, an adaptive strategy and an agent model are adopted, a sample point set can be driven to be concentrated near an optimal solution on the basis of reducing the operation cost, the calculation precision of the agent model in the region of interest is further improved, and the optimization convergence difficulty is reduced. For pneumatic cutting optimization of the flexible inflatable wing structure, a high-precision global optimization algorithm is selected, the calculation efficiency is ensured, and falling into a local optimal solution is avoided.

A discretized traffic state discrimination method based on deep learning belongs to the technical field of traffic state discrimination. The method includes the following steps: step a, using the monitoring equipment installed in each direction of the intersection to collect the traffic status of the intersection at multiple different moments, and correspondingly obtain multiple sets of traffic status information; step b, according to the discretization coding process The information is described by discretization encoding respectively, corresponding to the discretization encoding data of the intersection at different times; step c, constructing a traffic state discrimination model based on deep learning according to the discretization encoding data obtained in step b; step d, using step c The constructed traffic state discriminant model is used to discriminate the traffic state. Through this discretized traffic state discrimination method based on deep learning, the traffic state can be comprehensively and truly described, no need for experts to participate in the selection of traffic state features, and the construction of the traffic state discrimination model can be realized automatically under semi-supervision.

A graphical user interface system that visually represents a graph node having multiple input ports, and that automatically adjusts the number of input ports to the graph node as open input ports are connected to upstream graph node(s) and / or as used input ports are disconnected from upstream graph node(s). Upon detecting that a set of one or more input ports has just been connected to one or more upstream graph nodes, the system may automatically add one or more additional input ports to the visual representation of the graph node without explicit user instruction. Upon detecting that a set of one or more of the input ports has just been disconnected from one or more upstream graph nodes, the system may automatically remove the determined one or more input ports from the visual representation of the graph node.

The present invention provides a method and device for adaptively constructing an indoor three-dimensional scene. The method includes: establishing object association diagrams corresponding to different scene categories according to marked indoor layout diagrams; selecting corresponding targets according to room information and object association diagrams input by users Indoor objects; generate the target indoor layout according to the preset room parameters input by the user and the marked indoor layout; construct the indoor 3D scene according to the target indoor objects and the target indoor layout. The indoor three-dimensional scene self-adaptive construction method and device provided by the present invention improve the efficiency of three-dimensional scene construction.

The invention discloses a digital twin method and system based on 3D model matching. The method includes four steps: model and texture training, model matching, texture fusion, and scene placement; wherein, model and texture training is an offline preprocessing step, and model matching, texture Fusion and scene placement are real-time processing steps. The training of the model uses multi-viewpoint silhouette images to learn the 3D structure, and realizes the 3D reconstruction of the polygonal mesh; the training of the texture obtains the texture flow through a fixed UV mapping, and realizes the reasoning from the 2D image to the 3D texture. Model matching uses the reconstructed model and the database model to perform IOU iterative calculation, and obtains the model whose IOU value is closest to 1 as the specified model after matching. Texture fusion is to fuse the specified model after matching with the 3D texture stream after texture inference to form a standard 3D model. Scene placement is to place the 3D model accurately in the 3D scene. This digital twin method automatically generates 3D model scenes and improves the efficiency of digital twins.

The invention relates to a construction method for a Chinese semantic knowledge base, in particular to a machine translation-based construction method for a Chinese semantic knowledge base.The problems that Chinese semantic knowledge bases are insufficient and the labor cost and the time cost are high in the prior art are solved, and the performance of semantic knowledge base translation based on cross-language mapping is improved.The method comprises the steps that 1, a source language end corpus annotated with the entity is obtained; 2, the subject distribution of the entity is obtained through calculation according to a subject model; 3, the translation probability of the entity in the source language end semantic knowledge base is extracted from a phrase translation table according to a source language end entity word list and marked as a P (tj|si); 4, an entity translation model based on source language end semantic knowledge base graph structure information is built.The construction method is applied in the field of construction of Chinese semantic knowledge bases.