756 results about "Auto-configuration" patented technology

The invention provides an intelligent agent automatic generation and scheduling system based on an artificial intelligence large language model. The system comprises an intelligent agent configuration module driven by the large language model, a workflow engine and automation module and a front-end and rear-end integration module. The agent configuration module driven by the large language model realizes automatic configuration of an agent and a workflow based on the large language model, and comprises a large language model interaction layer and an agent configuration module; the workflow engine and automation module is responsible for execution logic of workflow, supports multi-task parallel processing and comprises a workflow engine module and a task scheduler; the front-end and rear-end integration module realizes cooperative work of a JavaScript front end and a Python Django rear end by designing a unified data interface, the front end is responsible for interacting with a user and displaying an execution state of a workflow, and the rear end provides service logic processing and data persistence.

The invention relates to the technical field of telecommunication, in particular to a switch automatic configuration method and system and a medium. The method comprises the following steps: obtaining switch resource configuration data, and carrying out semantic enhancement topological graph modeling to obtain a network environment digital twinborn model; performing configuration instruction analysis based on the network environment digital twin model and a preset configuration management database to obtain an intention configuration semantic set; performing multi-manufacturer semantic mapping arrangement based on the configuration strategy path of the intention configuration semantic set to obtain a native configuration command set; performing identity path integrity auditing on each configuration command in the native configuration command set to obtain a signature command set passing verification; uploading the verified signature command set to a switch management platform to execute the command; and acquiring real-time behavior state data of the switch, and performing semantic deviation calculation to obtain a configuration result report. According to the invention, the effectiveness and adaptability of switch configuration can be improved.

The invention discloses an automatic configuration method and system for an electric energy quality monitoring terminal supporting multiple protocols, and the method comprises the steps: obtaining a communication data packet through the establishment of communication connection between a terminal and a configuration system, and carrying out the protocol recognition through the combination of statistical characteristics and structural characteristics. According to the method, the hierarchical decision tree is innovatively adopted to identify the protocol characteristics, protocol family identification and specific protocol type determination are realized through the preset protocol mapping template, and a new protocol can be automatically processed. The system comprises a communication module, a feature extraction module, a protocol identification module, a configuration instruction module and an execution module, and all the modules work cooperatively to achieve automatic configuration of the terminal. The technical problems that the power quality monitoring terminal is difficult to configure in a multi-protocol environment, the protocol identification efficiency is low, and the new protocol adaptation is complex are solved.

The invention relates to a collaborative autonomous perception and navigation method in a denial environment, which comprises the following steps: constructing a self-organizing robust communication system to realize dynamic networking and data sharing among multiple unmanned aerial vehicles in the denial environment, and adopting a self-adaptive network protocol to realize automatic configuration of a communication network under network topology change or communication interference; based on a multi-sensor fusion sensing system, environment information and motion information of the unmanned aerial vehicle are processed through a data fusion algorithm; a single unmanned aerial vehicle constructs a reward function based on unmanned aerial vehicle energy consumption, an exploration area, a path overlapping degree and a path danger degree, executes autonomous perception and exploration in an unknown environment and completes mapping; the distributed multiple unmanned aerial vehicles carry out individual communication and game playing in the unmanned aerial vehicle cluster according to map information, respective positions and working states, task distribution is achieved, and path planning and action decision making are completed. According to the invention, autonomy and collaboration of the unmanned aerial vehicle in a denial environment are improved, and an effective solution is provided for navigation in a complex environment.

Various systems and methods are presented regarding monitoring and controlling operation of a process. A visual representation of the process can be created based on a supermodel comprising models (representing one or more devices) and nodes (representing respective device variables and constraints). Further, the process can be represented by levels, wherein devices at each level can be self-aware and have onboard artificial intelligence, such that a device at any level can auto-configure itself in accordance with a requirement placed upon it. Field-level devices (IFLDs) can be smart devices which auto-configure based upon a requirement from a higher-level device. Accordingly, system awareness can be incorporated across all levels of the process enabling overall and device-specific optimization of the process. IFLDs can auto-configure to collect and transmit data in accordance with an instruction from a higher-level device, leading to efficient data collection, reduced data bandwidth / processing, and expedited system optimization.

The invention discloses a large language model reasoning method based on an unloading pipeline, and the method comprises the steps: obtaining an optimal unloading reasoning strategy through calculation according to the obtained model structure information and model configuration information of a large language model, and the hardware specification information and system operation load information of reasoning equipment; and then tasks in the optimal unloading reasoning strategy are scheduled through a fine-grained pipeline to output an unloading reasoning result of the large language model. According to the method, reasoning tasks are automatically configured according to input large language model information and a system hardware environment, and hardware resource use and reasoning performance are optimized. For deployment of a large language model on local equipment, transmission optimization is carried out for unloading using a solid state disk, so that the data transmission speed is increased. Meanwhile, fine-grained assembly line task scheduling is carried out for unloading reasoning, and the reasoning concurrency and the model throughput can be remarkably improved through unloading reasoning of an assembly line model.

Computerized systems and methods are disclosed for automating Configure to Order (CTO) and Quote to Order (QTO) processes. Methods include receiving user inputs for desired product configurations, retrieving corresponding data from a bill of materials database, and calculating optimized pricing through intelligent rules based on real-time market data. Automated quotes are generated and transferred to orders in a vendor system, selected based on pre-set criteria like vendor reputation and delivery time. Validation steps reduce errors, and real-time reports are generated. The system integrates a Real-Time Data Mesh for data aggregation, a Single Pane of Glass User Interface for user interactions, and Advanced Analytics and Machine Learning Modules for implementing rule-based and learning algorithms. The system is accessible across various devices and standardizes data for uniform consumption, while also employing machine learning models to continually optimize processes. Notifications are sent to users upon successful execution of orders or completion of quotes.

Various systems and methods are presented regarding monitoring and controlling operation of a process. A visual representation of the process can be created based on a supermodel comprising models (representing one or more devices) and nodes (representing respective device variables and constraints). Further, the process can be represented by levels, wherein devices at each level can be self-aware and have onboard artificial intelligence, such that a device at any level can auto-configure itself in accordance with a requirement placed upon it. Field-level devices (IFLDs) can be smart devices which auto-configure based upon a requirement from a higher-level device. Accordingly, system awareness can be incorporated across all levels of the process enabling overall and device-specific optimization of the process. IFLDs can auto-configure to collect and transmit data in accordance with an instruction from a higher-level device, leading to efficient data collection, reduced data bandwidth / processing, and expedited system optimization.

In an embodiment, a method comprises: generating a user interface configured to allow selecting a product from a plurality of products that are customizable and displaying the user interface on a display device of a user computer; receiving, via the user interface, a selection of a particular product, from the plurality of products, that require customization; in response to receiving the selection of the particular product, automatically generating a plurality of customization options available for customizing the particular product; receiving one or more triggers of a plurality of triggers, generated based on customization options selected from the plurality of customization options; automatically generating one or more corresponding customization attribute values for the particular product; automatically generating one or more digital representations of the particular product, and displaying the digital representations of the particular product on the display device of the user computer.

The invention discloses a cross-cluster Dores unattended data migration method which comprises the following steps: acquiring metadata of a to-be-migrated table by connecting a source Dores cluster, analyzing and adjusting table structure features incompatible with a target cluster in the metadata, generating a compatible table establishment statement, and establishing a target table in the target cluster; an API of a data migration platform is called through a preset interface, a migration task is automatically configured and submitted, and the migration task comprises a source table, a target table and table association information; polling a task state in real time, and triggering a next migration task or an exception processing flow according to a task execution result; processing of all the to-be-migrated tables is executed in sequence according to a preset rule, and the number of concurrent tasks is limited to maintain cluster stability; and after migration is completed, performing multi-dimensional data consistency verification on the source table and the target table, and triggering a repair process according to a verification result. According to the cross-version Dores database migration method and device, the efficiency and reliability of cross-version Dores database migration are improved, and manual intervention and operation errors are effectively reduced.

The invention discloses an I2C bus system for configuration of a plurality of circuit structures, the I2C bus system comprises a plurality of circuit structures connected to an I2C bus, and the circuit structures are used for configuring I2C address device information according to detection pins set by the circuit structures; the I2C address device information comprises device addresses, and the device addresses configured by any two circuit structures are different; wherein the mapping relations about the I2C address equipment information used by the plurality of circuit structures are the same. By providing corresponding detection pins in the circuit structures connected to the I2C bus and detecting signals at the pins in real time, I2C master-slave roles and device addresses of all the circuit structures are automatically configured, and personnel in related technical fields do not need to burn matched firmware for all the circuit structures according to set welding positions when leaving a factory. Even if the welding position is wrong, the correct device address configuration of each circuit structure in the I2C bus is not influenced, and the production process of the chip supporting I2C communication is simplified.

The invention discloses an integrated machine learning model pre-labeling method and system. The method comprises the following steps: S1) importing data; s2) model selection and matching; s202) multi-model selection and automatic optimization: comprehensively selecting an optimal model based on a selection strategy of data features and task complexity; s3) automatic configuration of the model; S4) pre-labeling of the model; s5) performing manual auditing and correction; and S6) outputting a labeling result. S7) performing model performance evaluation, and automatically adjusting hyper-parameters; s8) updating a model recommendation strategy through a random forest algorithm; the system comprises a user module, a data import module, an annotation type selection module, a model configuration module, an annotation module, an auditing and adjusting module, an annotation result output module and a model adjusting module. According to the method, the machine learning model is integrated to realize pre-annotation of the data, meanwhile, the recommendation algorithm based on the annotation type is designed, the machine learning model is recommended according to the annotation type selected by the user, and the annotation accuracy and speed are improved.

Teachings of the present disclosure include methods and systems for automatically configuring and deploying a containerized application. An example method includes: obtaining source code associated with a containerized application; generating an integrated configuration file based on the source code, and constructing, with the integrated configuration file, a component associated with the source code; generating an image configuration file based on the source code and the integrated configuration file, and generating, with the image configuration file, a container image associated with the source code; generating an application configuration file based on the source code, the integrated configuration file, and the image configuration file; and generating the containerized application using the application configuration file and the container image.

The invention relates to the technical field of large model data processing, in particular to an agent automatic configuration method and system based on a large model, a knowledge base and a tool, and provides the following scheme: obtaining training data, inputting a natural language into an inference model to generate a query task set, and after optimization, inputting the query task set into an Embedding model to generate a preliminary retrieval result set; the optimization result is input into a reordering model to generate a final retrieval result; and when the training conditions are met, packaging the inference model, the Embedding model and the reordering model into an intelligent agent. The system consists of an inference model configuration module, a retrieval model configuration module and a reordering model configuration module, and cooperatively realizes task analysis, semantic retrieval and result optimization. The method improves the retrieval accuracy and efficiency, and is suitable for knowledge base question answering and complex data processing scenes.

The invention discloses an AI-based software compatibility test system and method, and belongs to the field of software testing, and the method specifically comprises the steps: collecting historical test data, market demands and product update information, predicting compatibility test demands by using a machine learning algorithm, automatically distributing and scheduling test tasks, monitoring a test environment in real time, and automatically configuring the test environment; different use scenes are simulated, when an automatic test script is executed, the progress is monitored in real time, abnormity is processed, and the system generates a detailed test report by learning a test rule, positioning a compatibility problem, adjusting a test strategy and optimizing product configuration, so that the test efficiency and accuracy are improved, and intelligent management of the test process is realized.

Various systems and methods are presented regarding monitoring and controlling operation of a process. A visual representation of the process can be created based on a supermodel comprising models (representing one or more devices) and nodes (representing respective device variables and constraints). Further, the process can be represented by levels, wherein devices at each level can be self-aware and have onboard artificial intelligence, such that a device at any level can auto-configure itself in accordance with a requirement placed upon it. Field-level devices (IFLDs) can be smart devices which auto-configure based upon a requirement from a higher-level device. Accordingly, system awareness can be incorporated across all levels of the process enabling overall and device-specific optimization of the process. IFLDs can auto-configure to collect and transmit data in accordance with an instruction from a higher-level device, leading to efficient data collection, reduced data bandwidth / processing, and expedited system optimization.

The invention relates to the field of vehicle-mounted bus testing, and discloses a vehicle-mounted CAN bus terminal resistor configuration method and system for node testing, and the method comprises the steps: obtaining a node identifier and a terminal resistor identifier corresponding to each test node in a vehicle-mounted CAN bus test, the terminal resistor identifier being used for identifying the terminal resistor access state of the test node; obtaining a first node position of a first test node corresponding to the first node identifier, configuring a terminal resistor for the first test node when the first node position is an end node of the vehicle-mounted CAN bus, and canceling the configured terminal resistor for the test node of a non-end node; and updating the terminal resistor identifier of each test node according to the terminal resistor access state corresponding to each test node. According to the invention, the terminal resistor can be automatically configured in the CAN bus test.

The invention relates to the technical field of communication systems, and discloses an AC / AP (Access Point) centralized management system and method based on an MQTT protocol, and the system comprises a DHCP (Dynamic Host Configuration Protocol) server which is responsible for distributing an IP (Internet Protocol) address for a plurality of AP access points, and sending an MQTT server address of an AC access module to the AP access points according to a configured option field. And after acquiring the MQTT server address, the AP access point establishes connection with the MQTT proxy based on the MQTT protocol, and sends registration information to the AC access module to complete access registration. In addition, the AP access point further sends operation data to the AC access module according to a preset frequency. And the AC access module issues configuration and management instructions to the plurality of AP access points by using the MQTT proxy, and performs evaluation according to the operation data sent by the AP access points. And according to the evaluation result, the AC access module determines whether to adjust the access state of the AP access point. According to the invention, the automatic configuration and management of the AP access point are realized through the DHCP server and the MQTT protocol, so that the efficient performance and the real-time performance of the network are effectively ensured.

The invention relates to the technical field of power electronic conversion, and discloses a high-efficiency rectification conversion system and a control method thereof, and the system comprises the following modules: a detection module, an input compatible module, a hybrid power device module, a control module, a thermal management module and a frequency modulation module. The control method comprises the following steps: acquiring input power grid voltage, output current and load state parameters; calculating an input voltage phase difference; dynamically selecting the type and channel configuration of the silicon carbide or gallium nitride power device according to the load rate; outputting a device configuration instruction and a switching frequency control instruction; adjusting the cooling system through the evaluated thermal state of the conversion system; and the control module receives the control instruction output by the control module and is used for implementing a corresponding pulse width modulation strategy. According to the method, a multi-system power grid identification and self-adaptive topology switching strategy is adopted, the technical effect of automatically configuring the optimal rectification architecture under different input types is achieved, and the problems of response delay and poor compatibility of the method in the environment of variable power grid types are solved.

The invention discloses a ground station intelligent equipment management and control system and method for spaceflight measurement and control, and the system comprises a data collection and display module, an intelligent scheduling module, a task execution module, a receiving and forwarding module and the like. Providing a measurement and control plan conflict resolution scheme; satellite macro parameters are configured and automatically issued; receiving, storing, cleaning and forwarding telemetering and remote control data in real time, and generating and pushing a measurement and control task operation report; all the modules cooperate with each other to automatically execute a measurement and control task. Through conflict detection and automatic resolution of the intelligent scheduling module, macro parameter automatic configuration / issuing / unloading of the task execution module and data autonomous processing of the receiving and forwarding module, full-automatic execution of the measurement and control task is realized, the task execution efficiency is improved, manual operation errors are avoided, and the spaceflight measurement and control task efficiency is remarkably improved.

The invention relates to the technical field of optical line terminal configuration, in particular to a method and system for automatically configuring optical line terminals of different manufacturers based on artificial intelligence. The method comprises the steps of collecting multi-source heterogeneous data to train a deep learning model, constructing a Transform or RNN-based architecture of a TensorFlow framework, performing cross validation and model compression, then performing optimization through a TensorRT inference engine, developing an intelligent configuration application system, deploying the intelligent configuration application system to a control host, and providing algorithm support for automatic configuration. By constructing an automatic configuration system based on artificial intelligence, the problems of heterogeneous compatibility and intelligent configuration of OLT equipment of multiple manufacturers are systematically solved. In a configuration optimization link, a virtual simulation environment is constructed based on a real network topology, a configuration effect is evaluated through multi-dimensional indexes such as throughput and time delay, potential conflicts are detected in combination with an AI algorithm, an optimization scheme is generated, and the configuration error rate of manual operation is reduced.

Various systems and methods are presented regarding monitoring and controlling operation of a process. A visual representation of the process can be created based on a supermodel comprising models (representing one or more devices) and nodes (representing respective device variables and constraints). Further, the process can be represented by levels, wherein devices at each level can be self-aware and have onboard artificial intelligence, such that a device at any level can auto-configure itself in accordance with a requirement placed upon it. Field-level devices (IFLDs) can be smart devices which auto-configure based upon a requirement from a higher-level device. Accordingly, system awareness can be incorporated across all levels of the process enabling overall and device-specific optimization of the process. IFLDs can auto-configure to collect and transmit data in accordance with an instruction from a higher-level device, leading to efficient data collection, reduced data bandwidth / processing, and expedited system optimization.

The invention discloses a method and equipment for automatically configuring a branch monitoring device and a storage medium, and relates to the technical field of digital information transmission, and the method comprises the steps that the branch monitoring device sends a periodic broadcast information packet through an Ethernet interface; the control module obtains the periodic broadcast information packet through the first network switch; constructing an equipment file corresponding to the branch monitoring device on configuration software of a control module according to the periodic broadcast information packet; determining the parameter configuration corresponding to the branch monitoring device in a parameter configuration library table according to the equipment file, and unicast the parameter configuration to the branch monitoring device through the first network switch to complete the configuration of the corresponding parameter of the branch monitoring device; and after determining that the parameter configuration is successful, the branch monitoring device performs equipment self-inspection and display self-inspection according to a self-inspection instruction sent by the control module, and generates a detection report. Through combination of software and hardware, the technical problem of low configuration detection efficiency of the device is solved, and the configuration detection efficiency of the device is improved.

Techniques for wildcard based private application access are disclosed. In some embodiments, a system, a process, and / or a computer program product for wildcard based private application access includes receiving a request for access to an application over a secure access service edge (SASE) network for a user associated with an enterprise; determining if the request for access to the application matches a wildcard (e.g., the wildcard can be configured by an administrator of the enterprise for matching a fully qualified domain name (FQDN) for the application); and automatically configuring access information (e.g., IP address, protocol, and destination port) for the application that matches the wildcard.

A method for automated deployment of application servers in a contact center system according to one embodiment includes generating a deployment package for the application servers in the contact center system based on deployment sizing information and environment information associated with the contact center system preparing a temporary deployment server of the contact center system for deployment of software to the application servers, and installing the software to the application servers using the temporary deployment server.

The invention provides a method, a controller and a system for automatically configuring a spanning tree protocol in a K8s cluster based on a DPU, and the method comprises the steps: monitoring whether the configuration data of a spanning tree protocol configuration instance in the K8s cluster is changed in real time, if yes, updating a bridging device table of a virtual switch database according to the spanning tree protocol configuration instance, and if not, updating the bridging device table of the virtual switch database; sending the updated spanning tree protocol configuration data to a virtual switch in the DPU so that the virtual switch in the DPU receives the updated spanning tree protocol configuration data and correspondingly configures or starts a corresponding spanning tree protocol STP and / or a rapid spanning tree protocol RSTP; and monitoring whether the virtual switch configures or starts the STP and / or the RSTP in real time, and if yes, updating the state of the custom resource definition unit for the spanning tree protocol, so that a user can know the current spanning tree protocol setting state of the virtual switch. According to the invention, the automatic configuration of the spanning tree protocol in the K8s cluster can be realized, the real-time performance and reliability of the automatic configuration can be effectively improved, and the efficiency and quality of network operation and maintenance can be effectively improved.

A set of discrete input / output (I / O) channels for one or more field devices may be grouped, organized, and connected to a field module device, which may connect to an electronic marshalling apparatus in a marshalling cabinet via an I / O channel. The field module acts as an intermediary, decoding messages received via the I / O channel to identify commands for discrete output (DO) channels that are then forwarded appropriately. The field module may also receive variable values carried by signals on discrete input (DI) channels and encode the values to a message that may be transmitted to the marshalling apparatus and controller, thus making the variable values on the DI channels available to the controller. The field module may store a profile including information that facilitates various smart commissioning techniques, including autosensing of tags, automatic tag binding, and automatic configuration of a control element corresponding to the field module.

The invention discloses an automatic configuration method and system for a power supply loop, and relates to the technical field of intelligent power distribution. After a plug device is rotationally locked, an identity is read in a near field, and corresponding voltage and power templates are called; inputting the power template and bus real-time current into an edge algorithm to obtain residual capacity and generate an initial power distribution matrix; when the residual capacity is higher than a safety threshold value, a phase sequence, a breaking value and overcurrent delay are issued to the intelligent circuit breaker, and zero-voltage window spark-free closing is realized; during operation, load change is predicted, time dislocation and power coupling parameters are calculated, a peak regulation coefficient is obtained through fuzzy reasoning, and a non-critical load migration stabilizing peak value is triggered; and finally, synchronizing the identity, the power distribution matrix and peak regulation parameters to the digital twin model, and realizing self-learning, energy efficiency improvement and system stability improvement by means of a parallel simulation optimization rule and second-level multiplexing during similar access.

The invention discloses an automatic configuration method for dispatching access of plant station equipment, and the method comprises the steps: A, obtaining communication data from the plant station equipment, and enabling the communication data to comprise a frame structure field; b, based on the frame structure field, identifying a communication protocol type by comparing an initial identifier, a function code field and a frame length field; c, in combination with the communication protocol type and the equipment attribute field, an access configuration strategy template is matched, and the template comprises a communication parameter set, an interface adaptation rule and a signal mapping relation; d, generating a structured configuration data file according to the configuration strategy template; and E, deploying the configuration data file to a scheduling system to complete equipment communication registration and data interaction initialization.

A peripheral device workspace cloud orchestrator executing at a cloud-based information handling system comprises a hardware processor to execute code instructions to determine a usage category from operational telemetry data for a current peripheral device workspace having an anchor node and current peripheral devices operatively coupled at a location, the usage category defined by a previous peripheral device operational telemetry data, previous manifest of previous peripheral devices within a previous peripheral device workspace, and at least one previous functional capability and previous adjustable operational configuration of a previous peripheral device. The hardware processor to determine a functional capability for a current peripheral device sufficiently matches the previous functional capability for the usage category and instructs the anchor node to automatically configure the current peripheral device according to the previous adjustable operational configuration in that usage category.