319results about How to "Improve deployment efficiency" patented technology

The invention relates to the technical field of grounding monitoring, and discloses a multipath grounding monitoring method for an intelligent station electrostatic monitor, and the method comprises the steps: carrying out the infrared scanning of a station region, comparing a station layout template, obtaining the station configuration data, and reading an electrostatic monitoring parameter; performing time division multiplexing matrix design on the multiple monitoring channels to obtain a time division multiplexing configuration scheme; performing on-off control time sequence compilation on the high-speed solid-state relay to obtain an on-off control time sequence table, and executing intelligent on-off control to realize monitoring channel switching; inputting the electrostatic signals of the plurality of monitoring channels into a high-precision analog-to-digital converter for parallel sampling and de-noising processing to obtain pre-processed electrostatic data; according to the invention, the monitoring strategy can be dynamically adjusted according to the station characteristics, the efficient collection and processing of multichannel data are realized, and an accurate static risk assessment and early warning mechanism is provided.

According to the model virtualization deployment method and device, the storage medium and the computer equipment provided by the invention, after the target model selected by the user under the at least one model version of the at least one type created in advance is obtained, the reasoning framework and the at least one resource used when the target model is deployed can be determined firstly; creating a corresponding number of virtual instances according to the number of resources used when the target model is deployed, binding the virtual instances with a specified pod in the k8s service configured under the resources of the corresponding specification, and deploying the target model to the specified pod; in the process, the resources required by the model reasoning service are divided into different specifications in advance, the resources of each specification are configured with one k8s service, and each k8s service comprises a plurality of pods, so that a user only needs to select the resources of the corresponding specification according to the size of the model when deploying the model, and then the model can be deployed to the specified pods; and automatic deployment of the model is realized.

The invention discloses a large model deployment method and device for a heterogeneous platform, equipment and a program product, and relates to the technical field of artificial intelligence. A large model to be deployed is divided into a plurality of sub-models, and according to the operator type and the operator calculation amount contained in each sub-model, the operator support conditions of various types of chips on the heterogeneous platform are combined, so that the large model deployment efficiency is improved. The method comprises the following steps: determining a target chip to be deployed by each sub-model, determining a quantization strategy of each sub-model according to a quantization support condition of the target chip, quantifying the sub-model according to the quantization strategy, and generating a deployable sub-model from the quantized sub-model and the quantization strategy so as to be deployed into a corresponding target chip on a heterogeneous platform. And automatic deployment of a large model is realized. According to the method, the target chip to be deployed by the sub-model can be automatically selected in the large model deployment process, the quantization strategy can be automatically selected, and compared with a method of manually setting a deployment scheme, the deployment efficiency can be greatly improved, and the end-side deployment difficulty of the large model can be reduced.

The invention discloses a cloud platform rapid deployment system and method. The system comprises a Docker, a container arrangement tool, a database service, a cloud platform application, a monitoring and management tool, a network infrastructure and a security component. The Docker is responsible for managing the complete life cycle of the container and providing a virtualization environment; the container arrangement tool is used for managing and arranging a Docker container; the database service is used for storing information in the cloud platform and carrying out communication through the network service of the Docker; the cloud platform application is a set of service logic and functions deployed in a Docker container; the monitoring and management tool is used for monitoring a running state and managing log information; the network infrastructure is used for ensuring network interconnection between the servers and supporting network communication of the Docker container; and the security component is used for protecting the cloud platform from external attacks and internal threats. According to the method, the deployment process can be simplified, the deployment time is shortened, manual intervention is reduced, the deployment efficiency is improved, resources are optimized, and the operation cost is reduced.

The invention relates to the technical field of software code evaluation and conversion of heterogeneous multi-core chips, in particular to a code evaluation and conversion method and system applied to a heterogeneous multi-core chip and a medium. The method comprises the following steps: reading a configuration table to obtain hardware configuration information of equipment; constructing a simulation experiment environment in the corresponding configuration table; converting the software algorithm according to requirements; running a software algorithm in the simulation environment, enabling the algorithm to run on hardware with different hardware configurations through parameter setting, and obtaining technical indexes of algorithm running; analyzing and comparing performance indexes of the algorithm in different operation environments, and performing adjustment optimization and operation test on the algorithm; a software algorithm is deployed on specific hardware, and evaluation testing in an actual operation environment is carried out. According to the method, the performance of a software algorithm on a heterogeneous multi-core chip can be improved, the development cost is reduced, and the product development period is shortened.

The invention provides a method and device for deploying a large language model based on computing power of an intelligent computing center, and the method is applied to a VCluster cluster of the intelligent computing center, and comprises the steps: S1, obtaining a preset configuration file which comprises the name of a target large language model and the network address of a private cloud platform; s2, according to the name of the target large language model, obtaining an encapsulation file of the target large language model encapsulated in NVIDIA NIM service, and according to the network address of the private cloud platform, transmitting and storing the encapsulation file to the private cloud platform; and S3, deploying the target large model to the private cloud platform according to the packaging file. The target large model deployment method has high security and high deployment efficiency.

The invention provides a Serverless application development device and method based on WebIDE, and aims to solve the problems of inconsistent environment and low efficiency in Serverless application development. The device comprises a Serverless instance, a WebIDE component, a code debugging component, an environment storage component and a one-key deployment component. Wherein the Serverless instance comprises a cloud-based production environment and a test environment corresponding to the cloud-based production environment; the WebIDE component is arranged in the test environment; the code debugging component supports online debugging and testing; the environment storage component is used for storing configuration and change in the development process; the one-key deployment component can directly deploy applications in a test environment to a production environment. The method comprises the steps that a Serverless test environment is divided, a WebIDE assembly is arranged in the Serverless test environment, application development is carried out through the WebIDE assembly, online debugging testing is carried out through a code debugging assembly, configuration changes in the development process are stored through an environment storage assembly, and applications are directly deployed to a production environment through a one-key deployment assembly. According to the method, the Serverless application development and deployment efficiency is improved, and the consistency of a development environment and a production environment is ensured.

The invention discloses an electric two-wheeled vehicle flow-based regional battery swap station deployment method without historical data. The method comprises the steps of obtaining regional feature data and environmental data related to a battery swap station in a city; constructing and training a generation model based on an analysis result of the historical data of the deployed battery swap station area in combination with a de-noising diffusion probability model; constructing a battery swap station deployment optimization problem which enables the correlation between the number of battery swap stations and the two-wheeled vehicle area flow and the coverage area of the battery swap stations to reach the maximum balance; solving a battery swap station deployment optimization problem through a simulated annealing algorithm to obtain an optimal battery swap station deployment scheme; in the step-by-step solving process, calling the trained generation model to synchronously generate the electric two-wheeled traffic flow according to the regional feature data and the environmental data of the target region; and realizing the electrical changing station deployment of the target area through the optimal electrical changing station deployment scheme. According to the method, the accuracy and efficiency of solving the optimization problem of the electric swap station deployment and the practicability of the electric two-wheeled vehicle regional swap station deployment can be improved.

The embodiment of the invention provides an acquisition probe management system and method. The method can be used in distributed fields. The system comprises an acquisition probe deployment page management end, an acquisition proxy server end and an acquisition proxy end, the acquisition probe deployment page management end is used for providing a man-machine interaction function so as to create an operation task corresponding to operation task information based on the operation task information for an acquisition probe obtained by man-machine interaction; and sending the operation task to a collection agent server corresponding to the node, and displaying an execution state of the operation task, the acquisition agent server side is used for triggering the node to execute the operation task, and the acquisition agent side is deployed in the node; and the acquisition agent end is used for executing the operation task aiming at the acquisition probe. The method is used for achieving the effect of quickly deploying the corresponding acquisition probes to a plurality of servers and realizing unified management of the acquisition probes.

The invention discloses an equipment deployment method and device, computer equipment and a storage medium, and the method comprises the steps: building an equipment deployment optimization target, and determining a target function and a constraint condition; based on the equipment deployment information of the deployed project, key parameters are predicted through a preset neural network, and the key parameters are used as initial parameter values of a quantum ant colony algorithm; iterating the quantum ant colony algorithm for a preset number of iterations, and based on an objective function, calculating an objective function value corresponding to each equipment deployment scheme meeting the constraint condition to obtain a local optimal equipment deployment scheme generated in each iteration process; and selecting a global optimal equipment deployment scheme from all the local optimal equipment deployment schemes. The optimization target is solved through the neural network and the quantum ant colony algorithm, the equipment deployment scheme is determined, the labor cost can be reduced, and the equipment deployment efficiency can be improved.

The invention relates to a large-scale low-orbit satellite constellation network access node selection method, and belongs to the technical field of satellite communication. The method comprises the following steps: firstly, calculating positions and beam coverage conditions of high and low orbit satellites in an earth-fixed coordinate system at each moment through ephemeris, platform and load information of the satellites; secondly, designing an adaptability function according to the position relation between satellites, beam coverage, communication link channel quality and service demand conditions; and finally, a satellite suitable for serving as a network access node is selected from a large-scale low-orbit satellite constellation through a genetic algorithm. The method can be used for realizing efficient dynamic connection node selection in high-orbit and low-orbit satellite combined networking, so that functions of resource coordination, load balancing and the like among satellites are realized, and the deployment efficiency of a large-scale low-orbit satellite constellation is improved.

The invention provides a time slice configuration method and system for a secure real-time bus (SRB), which can be applied to the technical field of communication, and the system is composed of a management device and a plurality of SRB devices in ring topology connection. The management equipment sends a detection starting enabling message; and each SRB device sends the network address to two adjacent SRB devices. And the management equipment sends a detection output enabling message to the target SRB equipment, the target SRB equipment creates a link relation packet, and the logic address is stored in the link relation packet and transmitted to the next SRB equipment. And after the other SRB equipment receives the link relation packet of the previous equipment, adding the logic address and continuing to forward the link relation packet. And when the target SRB equipment receives the link relation packet containing the logic address of the target SRB equipment, the target SRB equipment sends the link relation packet to the management equipment, so that time slice distribution of all the SRB equipment is completed. And through automatic time slice configuration and management, the system deployment efficiency is remarkably improved. And high efficiency and real-time performance of network management are ensured.

The invention is applicable to the technical field of computer software, and provides an application deployment method, which comprises the following steps: acquiring code information of a to-be-deployed application; generating a mirror image file based on the code information, and storing the mirror image file in a mirror image warehouse; and under the condition that the mirror image file is stored in the mirror image warehouse, sending a deployment command to a second electronic device, so that the second electronic device logs in the mirror image warehouse based on the deployment command to download the mirror image file, generates a container based on the mirror image file, and deploys the application based on the container. Automatic deployment can be realized, so that the application deployment efficiency can be improved.

The invention provides a wired NVR (Network Video Recorder) and IPC (Internet Protocol Code) suit binding and code matching method, which comprises the following steps: when NVR and IPC equipment leave a factory for production, generating a globally unique suit mark TID for each pair of equipment; presetting a unique identifier UID of each IPC device and a default IP address in each channel of the NVR device; when the NVR and the IPC equipment are started and accessed to a network, the NVR equipment tries to be connected with the IPC equipment in the configured channel; until all the channels are successfully connected to the corresponding IPC equipment; in the code matching process, the NVR device broadcasts a code matching message in a wired local area network, the code matching message takes a TID as a key field, the IPC device receiving the code matching message stores TID information and returns TID / UID and other IP network information of the IPC device in response to the message, and therefore pairing and binding of the devices are completed through matching of the TID / UID. The invention aims to solve the problems that the binding operation of the NVR and the IPC is tedious, the efficiency is low and the corresponding relation cannot be accurately specified in a traditional wired network networking mode.

The invention discloses a cross-platform operating system upgrade patch automatic deployment method and system, and relates to the technical field of operating system patch management, and the method comprises the following steps: analyzing a patch dependency relationship, and dynamically adjusting a deployment sequence; performing isolation deployment based on a containerization technology; and monitoring the state of each container in real time, and performing real-time monitoring and feedback optimization on a deployment result. By means of the method, accurate control over patch deployment in a complex heterogeneous environment is achieved, the failure rate caused by dependency conflicts is reduced, meanwhile, deployment time is shortened, stability and reliability of system operation are improved, independence between patches is ensured, and the service life of the system is prolonged. According to the method and the system, system crash caused by patch incompatibility or operation failure is avoided, the deployment efficiency is improved, the efficient container isolation and highly compatible patch deployment process is realized, the self-adaptability and long-term stability of the system are improved, and powerful technical support is provided for complex and changeable patch deployment scenes.

The invention discloses a software deployment method and device, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: acquiring basic information of to-be-deployed software; according to the basic information, generating a code library interaction instruction, so that the software deployment system uses the code library interaction instruction to obtain the to-be-deployed software, and the software deployment system compiles the to-be-deployed software to obtain a corresponding mirror image file; and obtaining resource configuration information of the to-be-deployed software, and determining a deployed target container according to the resource configuration information, so that the software deployment system generates a deployment arrangement process for deploying the to-be-deployed software in the target container and executes the deployment arrangement process based on the mirror image file. According to the implementation mode, full-automatic software deployment is realized, the problem that manual intervention is needed in existing software deployment is solved based on the capability of generating the code library interaction instruction and automatically determining the target container, the deployment efficiency is improved, the deployment process is simplified, and labor force is liberated.

The invention discloses a data detection method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining a source program file; performing first data extraction processing on the source program file to obtain a target test function set; performing data segmentation processing on a plurality of target test functions in the target test function set to obtain word vectors corresponding to the target test functions; calculating the text similarity between the word vectors corresponding to each target test function to obtain a similarity calculation result; generating a plurality of test suites based on the similarity calculation result, and executing each test suite to obtain a running result log; and detecting unstable test data in the source program file according to the running result log. The method can reduce the repeated operation frequency of the test, improve the test efficiency of the detection system and reduce the execution time cost, and can be widely applied to the technical field of data processing.

The invention discloses an automatic high-precision assembly system and method based on visual feedback, belongs to the technical field of automatic assembly, and solves the problem that an existing scheme is insufficient in the aspects of automatic integration and actual usability. Comprising an embedded control unit, an XYZ Cartesian sliding table, a limiting sensor, a visual sensor, a visual mark and an upper computer processing unit, the embedded control unit is connected with the upper computer processing unit, and the embedded control unit is used for receiving a control instruction and feeding back state information. The embedded control unit is connected with a motor driver of the XYZ Cartesian sliding table and used for sending a motion control signal, and the embedded control unit is connected with the limiting sensor and used for receiving a switch signal. Working space boundary recognition and automatic calibration of the camera-robot hand-eye relation are achieved, the configuration and deployment process of a visual guidance system on the XYZ sliding table is greatly simplified, the requirement for professional skills of operators is lowered, and deployment efficiency is improved.

The invention relates to the field of mobile data communication services, in particular to a subway rail transit underground space emergency communication system and an arrangement method thereof. The subway rail transit underground space emergency communication system provided by the invention comprises a first communication link used for transmitting service data in a first state; the second communication link is used for transmitting service data in a second state; the communication link monitoring module is in signal connection with the first communication link and is used for monitoring the signal-to-noise ratio of data transmission in the first communication link; and the communication link switching module is in signal connection with the communication link monitoring module, is respectively in signal connection with the first communication link and the second communication link, and is used for switching the data transmission path from the first communication link to the second communication link according to the signal-to-noise ratio of data transmission in the first communication link. According to the invention, through double-link redundancy and rapid switching, automatic switching to a standby link is realized under abnormal conditions such as optical fiber faults or power interruption, and continuous and uninterrupted communication is ensured.

The invention provides a bastion host deployment method which can be applied to the technical field of information security and the technical field of finance. The method is applied to a deployment platform, and comprises the following steps: in response to a deployment request of a bastion host, obtaining a target configuration template under the condition of determining that a target configuration template corresponding to a deployment type contained in the deployment request exists in a configuration template library; under the condition that it is determined that the user operation data corresponding to the deployment type exists in the database, the user operation data are obtained, and the user operation data represent operation behavior data of a user corresponding to the deployment type; generating a target configuration file according to the target configuration template and the user operation data; and in response to a confirmation operation for the target configuration file, creating the bastion host for the user corresponding to the deployment type by using the target configuration file. The invention further provides a bastion host deployment device, equipment, a storage medium and a program product.

The invention discloses a communication scheduling method and device, equipment and a medium, and relates to the technical field of electronic price tags, and the method comprises the steps: determining a target communication module for each time period according to a communication duration type, a communication module identifier and a communication object in the time period; a communication instruction is sent to the target communication module, so that the target communication module responds to the communication instruction and communicates with a communication object corresponding to the target communication module, and the communication object in the future time period is determined according to the data type of the communication data; and according to the communication module identifier and the communication object in the future time period received from the target communication module, determining the communication duration type and the communication module identifier in the future time period, and enabling the target communication module and the communication object corresponding to the target communication module to stop communication. The deployment efficiency of the digital price tag system is improved, and the data transmission efficiency and stability in the communication process are improved.

The invention relates to the technical field of computers, and provides a method and device for automatically deploying a virtual machine software environment and a readable storage medium. The method is applied to a management node, a resource storage library is deployed in the management node, and virtual machine system mirror image resources, virtual machine software resources, virtual machine configuration files and software configuration files are stored in the resource storage library. Comprising the steps that target virtual machine system mirror image resources, target virtual machine software resources, a target virtual machine configuration file and a target software configuration file are determined and issued to a controller to be deployed; and controlling the to-be-deployed controller to execute the process of automatically deploying the virtualized software environment based on the target virtual machine system mirror image resource, the target virtual machine software resource, the target virtual machine configuration file and the target software configuration file. According to the method, the virtual machine software environment can be automatically deployed to one or more industrial controllers in various application scenes, so that the deployment time is shortened, the deployment efficiency is improved, and the deployment flexibility and universality are good.

The invention relates to the technical field of cross-modal retrieval, and discloses a cross-modal retrieval model training method and a cross-modal retrieval method.The training method comprises the steps that a cross-modal retrieval model is constructed; training the cross-modal retrieval model by adopting a low-parameter training method; integrating a Hash layer in the cross-modal retrieval model to learn Hash mapping; constructing a sorting order among training samples of the sorting perception loss optimization input cross-modal retrieval model; the retrieval method comprises the following steps: inputting a query sample into a cross-modal retrieval model; performing feature extraction on a query sample by the cross-modal retrieval model; the cross-modal retrieval model converts the extracted high-dimensional features into low-dimensional and continuous binary-like codes; the binary-like codes are processed and converted into binary codes; comparing the similarity between the binary code of the query sample and the binary code of a storage sample in a database; and outputting a retrieval result semantically related to the query sample. The method is high in retrieval efficiency and good in retrieval performance.

The invention discloses an installation method of an operating system, a cluster system, a server and a medium, and relates to the technical field of computers. And determining a server type and a target operating system corresponding to each client according to the identification information corresponding to the target demand, and configuring a startup mirror image corresponding to each server type. The server model is automatically identified through the identification information, so that the target operating systems of different platforms can be installed subsequently, the operating systems of specific types of platforms can be installed, and the operating systems of different platforms meeting target requirements can be installed subsequently in batches. According to the embodiment of the invention, each update object of the starting environment corresponding to the target operating system is packaged in a modular manner, and the whole operating system does not need to be manually deleted for updating during subsequent update iteration, so that the starting environment to be updated is determined in the modular manner; and running the to-be-updated starting environment to perform installation processing on the starting mirror image by using the packaged module information, thereby realizing version updating iteration operation, and improving the deployment efficiency of batch deployment and installation of the operating systems by the server.

The invention relates to the technical field of interface making, in particular to a personalized interface generation method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring historical use preference data of a user terminal; constructing a user portrait according to the historical use preference data; determining at least one interface component suitable for the vehicle model from a preset user interface component library, and creating a user terminal interface according to the at least one interface component; and adjusting the user terminal interface according to the user portrait. By adopting the method, the personalized interface of the vehicle end can be automatically created according to the specific label of the user, so that the purposes of optimizing the user experience and increasing the user stickiness are achieved.

The invention provides a multi-class machine abnormal sound detection method based on a diffusion model, and the method comprises the following steps: collecting normal sound data which comprises class information, and constructing a training data set; preprocessing normal sound data in the training data set to generate a Mel spectrogram, and generating labels corresponding to categories; training a multi-class abnormal sound detection network based on a diffusion model according to the labels corresponding to the classes and the Mel spectrogram; using the trained multi-class abnormal sound detection network to make mean-GMM features, and training a Gaussian mixture model; and inputting to-be-detected sound data into the multi-class abnormal sound detection network and the Gaussian mixture model to obtain a detection result. According to the invention, an abnormal score algorithm based on a Gaussian mixture model is designed, and the continuity and change characteristics of sound data in a time domain are uniformly considered. And an abnormal score with finer granularity is provided, and the detection accuracy and the adaptability to a complex industrial environment are remarkably improved.

The invention relates to a multi-round dialogue intention recognition method and device based on small sample learning, computer equipment, a computer readable storage medium and a computer program product, and can be applied to the technical field of computers. The method comprises the following steps: performing intention labeling processing on historical dialogue data in the insurance field to obtain a labeled data set; selecting a training data set for model training from the annotated data set according to the data volume of each intention category in the annotated data set; according to preset data sampling information, sampling from the training data set to obtain a support sample set and a query sample set; according to the support sample set and the query sample set, performing iterative training on a to-be-trained small sample intention recognition model to obtain a trained small sample intention recognition model; and according to a preset model framework, performing model conversion processing on the trained small sample intention recognition model to obtain a target small sample intention recognition model. By adopting the method, the intention recognition efficiency can be improved.

The invention discloses an application program deployment method and device, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: acquiring a dependent toolkit of an application program during running, and distributing a classification attribute corresponding to the dependent toolkit for the application program; generating dependency information of the application program based on the dependency toolkit, determining a compiling mode of the application program according to the classification attribute, compiling the application program according to the compiling mode, and generating a compiling package of the application program; and adjusting a deployment environment of the application program according to the dependency information, and deploying a compiling package of the application program in the adjusted deployment environment. According to the embodiment, standard and normalized application program deployment is realized, the influence of factors such as a programming language and an operation framework of the application program on deployment online is shielded, the deployment process is simplified, and the deployment efficiency is improved.

The invention relates to a box-type resident platform laying device applied to deep sea, and the device comprises a guide rail device which is used as a basic supporting structure of the whole laying device. The translation mechanism is arranged above the guide rail device, is in contact with the guide rail through a roller device and can freely roll on the guide rail; the turnover mechanism is hinged to the translation mechanism; the stop device is matched with the translation mechanism; and the anti-overturning device is matched with the overturning block of the translation mechanism. The box-type platform is compact and reasonable in structure and convenient to operate, and precise control over the box-type platform is achieved through the precisely-designed translation mechanism and the precisely-designed turnover mechanism. And the translation mechanism is made of a high-strength material and is tightly matched with the guide rail through the roller, so that the stability of the platform in linear motion is ensured. The overturning mechanism can stably overturn the platform from the horizontal state to the vertical state through the flexible hinge design and the advanced overturning driving technology, and powerful support is provided for the platform to smoothly descend into water.

The invention relates to the technical field of software systems, and particularly discloses a port operation scheduling system and method for high-concurrency businesses, and the scheduling system comprises a data processing module, a rule label field mapping module, a rule engine module and a scheduling module. The system has the beneficial effects that service rules can be created and modified according to real service management requirements through the rule engine module and stored in the rule base, the data processing module processes received data and matches corresponding rule labels, and the corresponding service rules can be quickly matched by identifying the rule labels; therefore, the corresponding scheduling instruction is generated, and the scheduling efficiency of the port facility equipment is improved.