573 results about "Information repository" patented technology

The invention belongs to the technical field of vehicle software testing, and particularly relates to a test case generation method and system based on big language model and rule collaboration, and the method comprises the steps: analyzing a demand document, and mapping the demand document to a fault ontology model to generate a structured test demand; generating a plurality of groups of fault verification conditions based on equivalence class division and a boundary value analysis method by utilizing a large language model; a multi-dimensional mixed retrieval strategy is adopted to retrieve a reference case from a historical case library; in combination with the verification condition, the reference case and the standardized information base, preposed environment settings, serialized operation instructions and expected responses of the test case are generated in stages; and finally, the case quality is ensured through cooperative verification of a large language model and a rule engine. The problems that a traditional method depends on manpower, the coverage rate is low, errors are prone to occurring, and historical knowledge is difficult to reuse are effectively solved, and the automation degree, accuracy and integrity of BMS test case generation are remarkably improved.

The invention relates to an unbalanced data-oriented electric power system lightning disaster risk detection method, which comprises the following steps of: S1, gridding a target detection land parcel to obtain a plurality of grid units; S2, based on latitude and longitude coordinates of each grid unit, obtaining line parameters and environment characteristics of each grid unit in combination with a line database and a geographic information base, wherein the line parameters comprise tower height, span, grounding resistance, loop number, lightning arrester number and transformer capacity, and the environment characteristics comprise soil conductivity, building height and land utilization type; and S3, inputting the line parameters and the environment characteristics of each grid unit into a trained first detection model to obtain the thunder and lightning probability and the maximum peak current of each grid unit. Compared with the prior art, the multi-source data such as the tower height, the span, the grounding resistance and the soil conductivity are comprehensively considered, and the risk assessment result has higher regional adaptability and accuracy.

The invention discloses an enhanced retrieval generation optimization method fused with a knowledge graph, and relates to the technical field of data processing. The method comprises the following steps of: constructing a knowledge graph containing entities, attributes and relationships from a data source, performing community division on the knowledge graph, and generating a multi-level community abstract for each community to form a structured abstract information base; a particle swarm optimization algorithm is adopted, joint optimization is conducted on the multi-modal retrieval mixed weight and the information filtering threshold value, the optimized multi-modal retrieval mixed weight and the optimized information filtering threshold value are obtained, and the multi-modal retrieval mixed weight comprises a vector retrieval weight, an atlas relation retrieval weight and a keyword retrieval weight; receiving a user query, and classifying the user query into a global query or a local query according to the semantic features; constructing an enhanced context according to a user query classification result; and inputting the enhanced context into a large language model to generate a final answer. According to the method, the self-adaptive optimization of the retrieval generation process is realized.

The invention discloses a data asset inventory and blood relationship analysis method, and belongs to the technical field of cloud computing and data asset management. The method comprises the following steps: constructing a unified asset information base by deploying a distributed acquisition agent cluster; performing unified semantic modeling on the metadata to generate a standardized data asset description file; analyzing the data processing log to construct a blood relationship map containing time sequence attributes and dynamic relationship strength; performing multi-dimensional anomaly detection and influence propagation analysis based on the atlas; and carrying out value evaluation and classification on the data assets in combination with topological importance, business value and risk level. According to the method, the problems of metadata dispersion, blood relationship static lag, abnormal influence assessment difficulty and the like in the prior art are solved, automatic checking, blood relationship dynamic tracking and asset value intelligent assessment of the data assets are realized, and the accuracy and decision support capability of data asset management are remarkably improved.

The invention relates to the technical field of creep age forming, in particular to an online monitoring and repairing method for creep age forming, which realizes closed-loop intelligent control of a creep age forming process by integrating acoustic emission real-time monitoring and electric pulse online repairing. According to the invention, real-time acoustic emission characteristic parameters are collected and extracted in real time, and damage initiation activities in the material can be captured immediately; the real-time acoustic emission characteristic parameters are compared with the creep aging damage information base in real time, and the current damage can be subjected to early recognition and accurate quantitative diagnosis according to historical damage evolution data, so that the damage type and the damage degree are accurately judged; and an optimal electric pulse parameter combination predetermined for the damage type and the damage degree of the target damage is called as a repair parameter, and electric pulse repair is immediately applied, so that damage self-adaptive accurate intervention is realized. And after repairing is completed, the process automatically circulates and returns to the monitoring step, and whole-process closed-loop control of damage monitoring, damage diagnosis and damage repairing is formed.

The invention relates to the field of combat command and dispatch, in particular to a multistage linkage combat unit command and dispatch system. According to the invention, a basic-level minimum emergency unit element information base is constructed through a data acquisition module; generating an electronic map supporting 2D and 3D switching; an intelligent analysis early warning module identifies abnormal conditions and generates early warning information; a plurality of multi-level linkage combat unit topology networks are generated through the multi-level linkage command architecture module; generating a command data large screen for dynamically aggregating public security indexes and a global situation visualization electronic map through a global situation visualization module; an early warning area is circled and selected through the intelligent scheduling module; and associating the corresponding multi-stage linkage combat unit to generate a deployment instruction. According to the multi-level linkage combat unit command and dispatch system provided by the invention, the multi-level linkage combat unit is effectively combined with a dynamic visual geographical environment from data acquisition, analysis and early warning to command and dispatch through cooperation of multiple modules, so that the command and dispatch efficiency is remarkably improved.

The invention relates to the technical field of electric power system risk perception, in particular to an electric power asset risk perception method and device based on a multi-dimensional time sequence and a large model and a medium, and the method comprises the steps: collecting asset fingerprints of an electric power information system, matching the asset fingerprints with a standard component knowledge base, and standardizing the asset fingerprints; obtaining a standardized asset fingerprint ledger library; extracting vulnerability feature information from the multi-source unstructured risk early warning information to obtain a structured risk intelligence information base; performing vectorization representation on asset features in the standardized asset fingerprint machine account library and vulnerability influence component features in the risk information library, calculating vector similarity between the asset features and the vulnerability influence component features, performing feature matching according to the vector similarity, positioning affected assets, and generating an asset risk list; and driving a risk disposal process through a process engine based on the asset risk list. The asset risk perception efficiency is improved, and the response period is shortened.

The invention discloses a centralized management system operation and maintenance server, which is deployed in a data center or a cloud platform and is used for performing centralized operation and maintenance management on target hosts in a plurality of service systems. The system operation and maintenance server comprises a resource registration module, a monitoring acquisition module, a configuration management module, a task arrangement module, an alarm and self-healing module, an operation and maintenance auditing module, an interface management module and an identity authentication and authority control module. The resource registration module is used for receiving information of a target host and a business system to which the target host belongs, generating a unique resource identifier and establishing a resource information base; the monitoring acquisition module issues a monitoring acquisition strategy based on the resource identifier and acquires monitoring index data and an operation log; the configuration management module performs difference comparison on the current configuration and the configuration baseline, and issues a configuration template and performs configuration version management after confirmation; and the task arrangement module arranges the atomic operation and maintenance operation into a task execution plan containing an execution sequence and a rollback strategy.

The invention discloses an auxiliary cadre recommendation method and system based on full-text-sparse-dense vector hybrid retrieval and big and small model collaboration, and the method comprises the steps: converting the original query of a user into a structured retrieval instruction based on a small-sample learning prompt project through a big language model; inputting the structured retrieval instruction into a trained post-post demand matching model, and analyzing and outputting a job condition set corresponding to the post; taking the job condition set as a retrieval condition, carrying out multi-dimensional parallel recall in the cadre information base through a triple mixed retrieval mechanism, and carrying out unified reordering on recall results to generate an ordered final cadre set; analyzing, optimizing and reasoning the final cadre set on the basis of a context prompt project and a large language model, and generating a final cadre recommendation scheme including man-post matching degree analysis; according to the method, intelligent and explainable cadre recommendation decisions can be realized, and the cadre selection efficiency, scientificity and objectivity are systematically improved.

The invention relates to a satellite computing power task deterministic transmission path selection method, which comprises the following steps: according to a computing power task type, a computing power resource use type and a computing power task calculation amount, in combination with computing power resource state information of each satellite computing power node in a computing power resource state information base, determining that a computing power task is calculated through a satellite computing power node, the tasks are decomposed into a plurality of tasks for cooperative calculation through a plurality of satellite computing power nodes; and taking the access satellite computing power node as a source node, taking the target satellite computing power node as a target node, and calculating a deterministic transmission path of the computing power task or each computing power subtask according to the end-to-end delay of the computing task and the network state information of each satellite computing power node in the computing power network state information base. The computing power task dynamic decomposition and the computing power task deterministic scheduling are adopted, the optimal matching of the computing power task and the computing power resource is realized, the reliable transmission of the computing power task in the controllable time is ensured, and the efficient calculation of various satellite computing power tasks is realized.

The invention discloses an intelligent review method for compliance of an electric power security supervision document, which relates to the technical field of electric power security management, and comprises the following steps: establishing a security supervision knowledge base and an expert information base, collecting electric power security supervision document text data and electric power operation field image data, extracting text semantic features and image features, and establishing a security supervision database; a document data risk identification model based on a long short-term memory network and an attention mechanism and a field operation risk identification model based on a rule reasoning technology are adopted to identify document violation information and field violation information, a supervision problem list is generated, and a self-optimization expert recommendation model based on reinforcement learning is established. And outputting a recommended expert list and a key supervision list. According to the invention, by constructing the multi-model collaborative intelligent examination method, the automatic analysis of the electric power security supervision document and the field image, the accurate positioning of violation information, the dynamic optimization matching of expert resources and the active pre-control of pre-risk are realized, and the efficiency of supervision work is comprehensively improved.

The invention provides a high-altitude phased array communication blind area electric power emergency unmanned aerial vehicle route planning method and system, and relates to the technical field of electric power emergency communication, and the method comprises the steps: 1, collecting environment data through a phased array communication device and an airborne environment perception sensor of an unmanned aerial vehicle, and constructing an environment information library; step 2, based on the environment information base, filling and boundary completion are carried out on irregular invalid areas in the polygon of the communication blind area, a continuous effective coverage boundary is formed, the dynamic communication blind area is identified and positioned, and communication characteristic parameters are extracted; and step 3, combining the communication characteristic parameters with preset phased array beamforming capability, unmanned aerial vehicle performance parameters and communication coverage requirements, and constructing a route planning model. According to the invention, the unmanned aerial vehicle can adaptively sense the change of a communication blind area in real time in a dynamic and complex power emergency rescue terrain environment, and the emergency response speed and the power emergency rescue efficiency are improved.

The invention relates to an intelligent airspace division method, system and device based on a live-action three-dimensional model and a medium. The method comprises the following steps: acquiring live-action three-dimensional model data, an airspace management rule base and an interest point semantic information base of a target area; on the basis of the interest point semantic information base, identifying and extracting key ground features of the live-action three-dimensional model data to obtain all ground features and corresponding attributes thereof; the attributes comprise surface feature types, three-dimensional geometric contours and space coordinates; based on an airspace management rule base, matching corresponding airspace management rules according to the types of the ground objects, and parameterizing the airspace management rules according to the three-dimensional geometric contours and the space coordinates to obtain management parameters corresponding to the ground objects; and based on the live-action three-dimensional model of each ground feature, generating a three-dimensional closed buffer body of each key ground feature according to each management parameter, and obtaining an airspace division model. By adopting the method, the pertinence and efficiency of airspace division can be improved.

The invention discloses a storage device and method for an artificial intelligence operation and maintenance robot, which are deployed in a data center or a cloud platform and are used for carrying out centralized operation and maintenance management on target hosts in a plurality of service systems. The system operation and maintenance server comprises a resource registration module, a monitoring acquisition module, a configuration management module, a task arrangement module, an alarm and self-healing module, an operation and maintenance auditing module, an interface management module and an identity authentication and authority control module. The resource registration module is used for receiving information of a target host and a business system to which the target host belongs, generating a unique resource identifier and establishing a resource information base; the monitoring acquisition module issues a monitoring acquisition strategy based on the resource identifier and acquires monitoring index data and an operation log; the configuration management module performs difference comparison on the current configuration and the configuration baseline, and issues a configuration template and performs configuration version management after confirmation; and the task arrangement module arranges the atomic operation and maintenance operation into a task execution plan containing an execution sequence and a rollback strategy.

The invention relates to a deployment recommendation method and device of wireless access equipment and computer equipment. The method comprises the following steps: acquiring deployment demand information of a user and physical deployment conditions of wireless access equipment in a target deployment area; according to the deployment demand information, screening out a candidate deployment scheme containing a network service package and matched wireless access equipment from a pre-constructed information base; the information base comprises a plurality of network service packages and equipment information of a plurality of wireless access equipment; for each candidate deployment scheme, determining a deployment position and a communication quality index value of each wireless access device under the candidate deployment scheme according to the physical deployment condition; and displaying each candidate deployment scheme, the deployment position corresponding to each candidate deployment scheme and the communication quality index value to the user. By adopting the method, the deployment efficiency can be improved, and collaborative optimization between the network communication quality and the economic cost is realized.

The invention discloses a carbon emission accounting information display system, and aims to improve the electric energy utilization efficiency of a novel electric power system, and the system comprises an edge calculation platform which carries out the network edge processing and data storage of terminal equipment; the load identification module is used for monitoring the type and the operation condition of a single load in a load cluster at a power inlet to obtain first data; the multiple space-time coupling module is used for establishing a carbon emission model and carrying out coupling association in space and time to obtain a coupled carbon emission flow model; the cloud center processes and calculates the first data to generate a data information base, and performs carbon emission data analysis based on a coupling carbon emission flow model; the visualization module is used for generating a data display graph according to the data information base and the carbon emission data analysis result; the problem that the identification degree is low due to load diversification can be solved, the equipment investment is effectively reduced while the load identification accuracy is guaranteed, and fine-grained electric power carbon emission calculation and carbon flow distribution display are achieved.

Disclosed in the embodiments of the present application are a task execution method, an electronic device and a storage medium, which are used for improving the efficiency of executing a task corresponding to a standard procedure. The task execution method comprises: receiving a task request; on the basis of the task request, acquiring a first standard procedure from a standard procedure information base; on the basis of the task request, acquiring a first sub-standard procedure from the first standard procedure, the first sub-standard procedure being a sub-standard procedure of the first standard procedure, the first sub-standard procedure being used for instructing a plurality of first sub-tasks to be successively executed on the basis of a jump relationship, the first sub-standard procedure comprising a first root node, and the first root node being used for instructing executing a start sub-task among the plurality of first sub-tasks; and, on the basis of the first sub-standard procedure, executing the plurality of first sub-tasks.

An adaptive user representation (AUR) system for use with generative artificial intelligence (AI) receives queries meant for the generative AI and utilizes one or more AI models to process each query to determine query context and to identify user information from a user information repository which is relevant to the query. The system generates instructions based on the query, query context, and the relevant user information for causing the generative AI to generate a response to the query which is personalized to the user. The AUR system transforms the raw data of the query and relevant user information into a set of instructions for the generative AI which describe how to personalize the response or required searches to ensure the final response is personalized.

A system described herein may output, by a Short Message Service Center (“SMSC”) and to a User Equipment (“UE”) information repository of a wireless network, a request to provide UE information, associated with a plurality of UEs, on an ongoing basis; receive, from the UE information repository and based on the request to provide the UE information on an ongoing basis, updated UE information associated with a particular UE of the plurality of UEs; maintain the updated UE information in a local UE information repository that is separate from the UE information repository of the wireless network; receive a Short Message Service (“SMS”) message associated with the particular UE; identify the updated UE information associated with the particular UE, as maintained in the local UE information repository; and forward the SMS message based on the updated UE information identified from the local UE information repository.

The invention provides a power grid interference monitoring and auxiliary diagnosis system. Based on a preset intelligent threshold value, when parameter fluctuation continuously exceeds 6dB, a data abnormity alarm is triggered, and hardware abnormity such as a sensor or a board card fault can be identified; calculating the total risk score of the power grid by quantitatively analyzing a plurality of parameters such as a voltage effective value, a frequency, a harmonic effective value, THD, low-frequency / radio-frequency conducted emission and a peak, and dividing the risk grades into'normal ', 'high risk' and'high risk '; the upper computer supports dynamic query, visual display and Excel export of historical data; an integrated interference auxiliary diagnosis function is combined with a typical database and a high-power equipment working condition information base, so that interference source equipment and abnormal frequency points can be automatically identified, and a diagnosis report is generated; the system is suitable for complex platforms such as ships and aircrafts, full-life-cycle electromagnetic compatibility management of a power grid is achieved, and the stability and safety of the system are improved.

A method for processing packets, the method comprising receiving a packet by a data processing unit (DPU), making a first determination that there is no exact match flow entry in a hardware switch pipeline in the DPU for the packet, in response to the first determination, classifying, in the DPU, the packet as a data packet, in response to the classifying of the packet: identifying, using a software data plane in the DPU, a forwarding information base (FIB) entry to be used to transmit the packet towards its intended destination, identifying, using the software data plane, a flow associated with the packet, initiating, using the software data plane, programming of an exact match flow entry in the hardware switch pipeline, and initiating, using the software data plane, transmission of the packet towards its intended destination using the FIB entry and the hardware switch pipeline.

The invention discloses a 5G and Beidou fused vehicle positioning navigation system. The system comprises a multi-source heterogeneous positioning module; a high-precision map and a dynamic traffic information base; a self-adaptive multi-layer map matching module; the dynamic path planning module considers steering limitation and real-time position feedback; and a central information fusion and decision unit. According to the invention, multi-source heterogeneous positioning data such as Beidou / GPS, 5G positioning, high-precision IMU, a vehicle-mounted atomic clock and a barometric altimeter are fused, and a tight combination algorithm based on ESKF or a factor graph is adopted, so that the system can realize accurate positioning in an environment with good satellite signals, partial shielding and even serious loss. Continuous, smooth and high-precision vehicle state estimation can be output, particularly when the number of visible satellites is insufficient, double-satellite positioning can be achieved by using the vehicle-mounted atomic clock to predict the clock error and combining the elevation constraint of the barometric altimeter, and the usability and robustness of positioning are improved.

The invention relates to the technical field of computer vision and artificial intelligence, and discloses a public area pedestrian trajectory monitoring system based on cross-camera tracking and hybrid simulation completion. The system comprises a camera array module, a pedestrian detection and cross-camera tracking module, a monitoring blind area information base module, a hybrid drive pedestrian simulation engine module, a track fusion and complementation module and a simulation integration propulsion module. According to the invention, monitoring blind area tracks can be effectively filled, track continuity and prediction accuracy are improved, existing hardware is fully utilized to reduce cost, and modular design is easy to integrate and convenient to use. The generated complete track can be widely applied to scenes such as public safety monitoring, passenger flow analysis and emergency evacuation plan making in public places such as ports, subway hubs, cruise ship wharfs and commercial complexes, and supports a real-time monitoring or post-analysis mode.

The invention discloses an unmanned aerial vehicle public benefit litigation analysis, research and judgment method and system based on deep learning, and relates to the field of computer research and judgment, and the method comprises the steps: analyzing an original data set through a pre-training deep learning model, recognizing an illegal behavior target, extracting the legal attribute of the illegal behavior target through combining with a laser radar point cloud, and generating a target list; on the basis of the target list, the identification of an illegal behavior target is inquired through a legal knowledge graph, a permission code and an authorized area in a permission information base are matched, legal behaviors are eliminated, a filtered target list is generated, and according to the filtered target list, a damaged ecological environment area in the multispectral image is segmented through a deep learning model. Fusing the laser radar point cloud and the historical laser radar point cloud to generate a three-dimensional terrain model, and calculating the area, volume and multi-dimensional ecological damage indexes of a damaged ecological environment region; according to the method, high-precision three-dimensional space analysis and multi-dimensional ecological damage evaluation are provided, and the credibility of public benefit litigation evidence is greatly improved.

The application provides a low-altitude airborne terminal heterogeneous network vertical handover method and system, the method comprises the following steps: constructing and dynamically updating a three-dimensional network coverage information library; predicting the future route of the airborne terminal based on its real-time motion state, and obtaining a candidate network set from the three-dimensional network coverage information library according to the prediction result; generating a handover decision weight for each network in the candidate network set based on a preset evaluation model; determining whether to trigger vertical handover through fuzzy logic decision based on the handover decision weight, the current network state and the operating parameters of the airborne terminal; if the vertical handover is triggered, performing a vertical handover operation based on the candidate network set and the handover decision weight. The application is based on the pre-collected network deployment information, combined with the actual flight information for vertical handover, the switching execution logic is simple and efficient, which can effectively avoid the communication interruption problem caused by switching failure or frequent switching, and significantly reduce the power consumption in the communication process.

The invention discloses a method for constructing an air pressure fingerprint model, and the method comprises the steps: carrying out the sampling based on known sampling equipment of horizontal positioning and vertical positioning, and obtaining the sample information; constructing a sample information base; defining an influence range of the sampling equipment, and performing grid division based on the influence range; fitting an air pressure base line of each grid according to the sample information base, wherein the air pressure base line is an air pressure reference value at a specified temperature and a specified height in the grid; sampling sample information in any grid based on a terminal device with known horizontal positioning, comparing the sample information with a preset environment semantic label template to obtain an environment semantic label of at least one grid, and constructing an air pressure fingerprint model, wherein the air pressure fingerprint model comprises an air pressure base line of each grid and an environment semantic label of at least one grid. According to the method, the standardized air pressure reference field is constructed and environment semantic intelligent labeling is realized, so that the environment perception precision in a complex scene can be improved.

Embodiments include a computing system, computing device, computer-implemented method and non-transitory computer readable medium for executing an artificial intelligence-driver negotiator. Embodiments obtain an information corpus corresponding to a claim event involving a user, and upon obtaining the information corpus, embodiments execute an artificial intelligence negotiator using the information corpus to perform automated negotiation process with the user.

The application discloses a substation maintenance system determination method, system, electronic equipment and storage medium. The method comprises the following steps: determining the power engineering information model corresponding to the current substation according to the environment information of the environment to which the current substation belongs; determining the device model information base corresponding to the current substation according to each power device, the power device identifier and the device association information of the corresponding power device located in the environment; determining the holographic display and operation and maintenance detection system for displaying the current substation and each power device located in the current substation; and determining the maintenance system applied to the substation based on the power engineering information model, the device model information base and the holographic display and operation and maintenance detection system, so as to simulate the maintenance of the power device based on the maintenance system. Based on the above technical scheme, the problem that the existing scheme cannot simulate the maintenance scheme when the power device is maintained and repaired, thereby causing high maintenance cost, long time and poor efficiency is solved.

The invention relates to a question and evaluation generation system and method fusing expert preference meta-cognitive intelligent agents, and belongs to the technical field of intelligent education. The system comprises an automatic question generation module used for calling a large language model to generate questions and evaluations according to a subject information base and an expert preference model; the meta-cognitive agent evaluation and optimization module is used for calling a meta-cognitive agent to perform multi-dimensional evaluation on questions and evaluation according to the expert preference model and generating an evaluation result and an optimization suggestion; and the expert interaction module is used for obtaining feedback information of the expert on the questions, the evaluation, the evaluation results and the optimization suggestions, and if the feedback information shows that the expert does not pass the verification, adjusting model parameters of the expert preference model, the large language model and the meta-cognitive agent according to the feedback information until the expert passes the verification. According to the invention, a deep cooperation mechanism between experts and artificial intelligence is established, artificial intelligence is guided to learn expert experience and preference through interaction, and high-quality questions and evaluation and assessment results are generated.

The invention provides a cognitive behavior intervention system assisted by multi-modal artificial intelligence recognition, which can acquire multi-modal information, realize deep feature fusion and analyze a cognitive behavior association mechanism, and comprises the following modules: a multi-modal data acquisition module for acquiring and preprocessing multi-modal data of a depression patient; the feature fusion module is used for extracting features of the preprocessed multi-modal data for feature fusion to obtain a cognitive state feature vector and a behavior mode feature vector; the cognitive behavior association module is used for constructing a cognitive and behavior association model to generate a cognitive behavior analysis report according to the cognitive state feature vector and the behavior mode feature vector in combination with a preset cognitive deviation type library and a behavior trigger factor library; and the personalized intervention module is used for generating a personalized cognitive behavior intervention strategy through a decision optimization algorithm based on multi-feature weighting according to the cognitive behavior analysis report in combination with a preset user basic information library and a cognitive behavior intervention scheme library.