1936 results about "Information system" patented technology

The invention provides a micro-grid cooperative scheduling method and device, and relates to the technical field of smart grids, and the method comprises the steps: obtaining historical operation data and real-time operation data of a micro-grid system, and data of an external information system; generating load demand and energy equipment output prediction information based on the historical operation data and the data of the external information system; constructing a layered multi-time-scale decision architecture, and performing decision optimization on each layer of agents by adopting a reinforcement learning algorithm; constructing a plurality of heterogeneous agents, and carrying out cooperative scheduling on the plurality of heterogeneous agents by adopting a centralized training and distributed execution multi-agent reinforcement learning algorithm; inputting the prediction information and the real-time operation data into a decision framework, and outputting a real-time control instruction; and setting a security constraint condition, and realizing optimization of the security constraint in combination with a Lyapunov function, a Lagrange multiplier method, a security layer mechanism and a reinforcement learning algorithm. According to the method provided by the invention, the safe, efficient and reliable operation of the micro-grid in the grid-connected / off-grid mode can be realized.

The invention discloses a battlefield target behavior prediction method capable of being guided by micro-physical representation and a thinking chain, and the method comprises the steps: obtaining satellite images, radar / communication detection and open source text multi-source time sequence data, completing the entity recognition, relation extraction and event detection, and constructing a dynamic space-time knowledge graph; the maneuverability, sensor detection, weapon range and terrain accessibility mechanism are micronized to serve as a physical consistency constraint embedded prediction model; generating an intention-action-result causal priori chain and parameterizing the causal priori chain into a computable structure; performing multi-branch long-time-sequence situation deduction, and outputting a future target behavior track and a scene probability; and evaluating and explaining by integrating the causal confidence coefficient, the physical consistency and the data goodness of fit, and giving a key event probability and situation evolution report. According to the method, unified modeling of semantic causal and physical constraints is realized, and the method has explainable, verifiable and robust prediction capabilities, and is suitable for target behavior prediction and command information system decision support in a complex environment.

The invention discloses an electric power information operation violation risk supervision system based on a knowledge graph, which relates to the field of violation risk supervision and comprises a dynamic graph construction module, a causal analysis module, a strategy analysis module, a strategy modeling module and a supervision decision module. The method comprises the following steps: obtaining multi-type electric power operation field sensing data and information system data, and carrying out data processing and knowledge graph dynamic construction to obtain a dynamic knowledge graph; performing risk situation quantification and risk decision point inference based on the dynamic knowledge graph to obtain a key causal decision point set; based on the key causal decision point set, through strategy logic analysis, obtaining a logic rule set which can be directly deployed and executed; according to the method, a logic rule set which can be directly deployed and executed is subjected to dynamic strategy evolution of a stochastic differential equation to obtain a dynamic strategy model, and the dynamic strategy model is subjected to decision optimal screening of measurement transformation to obtain an optimal supervision decision set, so that a risk value can be accurately calculated, and the supervision response speed can be increased.

The invention relates to an LLM-based power distribution network knowledge graph construction and fault intelligent diagnosis method. The method comprises the steps of constructing a knowledge system, constructing a normal operation state model and an anomaly detection threshold value, performing fault diagnosis through an LSTM-BP cascade network, and performing fault classification. The abnormal parameters and the fault classification result are input into an LLM model, the fault type is judged, corresponding diagnosis information is obtained, and the system generates a scheduling instruction and an emergency decision suggestion according to the diagnosis information; and generating a detailed diagnosis report. According to the system, statistical analysis and deep learning algorithms are adopted for operation parameters such as voltage and current after preprocessing, and automatic detection and fault classification of abnormal parameters are realized in combination with a CNN recognition module; a preset rule base in the knowledge system is combined to accurately determine a fault type, generate a scheduling instruction and an emergency decision suggestion, and assist operation and maintenance personnel in rapid response and dynamic management; finally, a detailed diagnosis report is generated, thereby improving the fault handling efficiency and the guarantee capability of safe and stable operation of a power grid.

The invention discloses a power distribution network fault differentiation operation and maintenance first-aid repair decision recommendation method, system and device based on a knowledge graph and a medium, and belongs to the technical field of operation and maintenance recommendation, and the method comprises the steps: obtaining the real-time monitoring data of a power distribution network, and constructing a fault feature data set; based on the fault feature data set, combining with a power distribution network knowledge graph to identify a historical fault entity; extracting a corresponding operation and maintenance first-aid repair strategy from the historical fault entity, presetting an evaluation index, and calculating a strategy effect score; evaluating a fault processing priority; and sorting the candidate first-aid repair strategies according to the strategy effect score and the fault processing priority, and screening and outputting a target operation and maintenance strategy suitable for the current fault and matters needing attention of the target operation and maintenance strategy. According to the method, the geographic information system is used for positioning the fault, the distance between the fault and the first-aid repair personnel is evaluated, the processing priority is determined in combination with the emergency degree of the fault, resource allocation is effectively optimized, and response efficiency is improved.

The invention provides an intelligent medical information system based on multi-system integration, a data security management method and device, electronic equipment and a storage medium, and is applied to the technical field of medical data processing. According to the method, three types of information including core security elements, multi-system heterogeneous adaptation (including HIS / LIS / EMR interface specifications and the like) and full-process auditing (including operation logs and the like) are obtained. Normalizing the core security elements by using technologies such as AI multi-mode privacy identification and the like to generate a standardized security baseline file; heterogeneous adaptation information is processed through a lightweight API connector and the like, and a multi-system security access scheme is formed. Associating the baseline file with the access scheme, and generating a full-life-cycle protection strategy in a zero-trust architecture; and processing the audit information to generate a dynamic security audit report. And finally, based on a security-adaptation linkage decision engine and compliance verification, outputting a cross-system data security sharing scheme and a privacy disclosure emergency response instruction, and realizing a medical data security management closed loop.

The invention discloses a wind generating set fault prediction method and system based on edge computing, and the method comprises the steps: collecting the vibration, temperature, rotating speed and other parameters of a wind generating set in real time through a data collection module deployed by edge computing equipment, carrying out the preliminary screening and packaging through a built-in data processing unit, and synchronizing to a constructed digital twinborn model; establishing an edge calculation fault analysis model based on model data, identifying potential fault features, comparing a physical unit operation state with a digital twin model simulation state parameter by parameter, performing preliminary diagnosis in combination with the fault features, evaluating a unit health state according to a fault mechanism model, and outputting a fault prediction result and part information. The system is correspondingly provided with six units including a data acquisition interaction unit, a data processing unit and a model construction updating unit, and all the units work cooperatively, so that accurate prediction and health management of faults of the wind generating set are realized.

The invention discloses a dynamic security authentication method for cross-platform information system integration, and relates to the technical field of cross-platform dynamic authentication. A non-tampering identity trust chain is established through a block chain consensus algorithm, the problems of single-point fault and expansibility of centralized identity management are solved, cross-platform unified identity verification is realized, the problem that multi-factor authentication lacks intelligent risk assessment is solved through intelligent contract automatic verification and user behavior analysis, threats can be dynamically responded, and the user experience is improved. The authority is dynamically adjusted based on the risk level, and a real-time access control decision engine is combined, so that the problem of response lag of traditional access control is solved, accurate authority control is realized, and finally, a continuously optimized security authentication mechanism and a unified and coordinated cross-platform security protection system are formed.

The invention discloses an intelligent medical record quality control method based on a rule and large language model hybrid engine, and relates to the technical field of natural languages, and the method comprises the steps: obtaining original electronic medical record data from a medical information system; performing post-structured processing on the original electronic medical record data, and converting an unstructured or semi-structured text in the original electronic medical record data into a unified structured data object readable by a machine; traversing a plurality of quality control points in a preset quality control rule base, and for each quality control point, adaptively selecting and executing a corresponding quality control path based on the converted structured data object; and based on the quality control results of all the quality control points, performing score calculation and generating a quality control report. According to the method, the automatic and deep quality control of the full-dose medical record can be realized, form inspection is covered, connotation logic analysis can be executed, the system is endowed with excellent flexibility and regional expansion capability, and reliable technical support is provided for improving the overall level of medical quality management.

The invention relates to the technical field of supply chain collaboration, in particular to a multi-level supply chain service ecological digital twin network collaborative optimization system which comprises a system and is used for building, optimizing and executing a supply chain digital twin network. The data acquisition module is used for acquiring physical entity data and service state data of a whole link of a supply chain in real time through an Internet of Things device and an information system interface; the data fusion and twinning construction layer is in communication connection with the physical perception layer and is used for carrying out fusion and standardization processing on the collected multi-source heterogeneous data and is based on a unified supply chain knowledge graph; according to the method, supply chain whole-process accurate mapping and real-time visualization are realized by constructing a multi-level digital twinborn body, automatic optimization is carried out among multiple targets such as cost aging carbon emission by applying an intelligent optimization algorithm, third-party service resources are dynamically scheduled based on a multi-attribute utility theory, cross-organization credible collaboration is realized by means of a block chain intelligent contract, and the service efficiency is improved. And a complete perception decision execution optimization intelligent closed loop is formed.

The invention provides a multi-agent collaborative decision-making operation and maintenance platform for an on-cloud electric power information system, which is suitable for integrated operation and maintenance of the on-cloud electric power information system, the operation and maintenance platform is in butt joint with a plurality of different on-cloud electric power information systems, and each on-cloud electric power information system is deployed with a plurality of agents responsible for different basic tasks. The operation and maintenance platform is composed of an operation and maintenance task making module, an agent calling module, a workflow generation module, a collaborative decision execution module and an operation and maintenance report distribution module. According to the operation and maintenance platform, multi-agent collaborative decision-making is realized, so that an operation and maintenance response mechanism is converted from passive discovery to active early warning, an execution mode is upgraded from manual driving to intelligent driving, knowledge management is evolved from scattered storage to structured reasoning, and the operation toughness, adaptability and intelligent level of a cloud electric power information system are comprehensively improved.

The invention relates to the technical field of system monitoring, and discloses an information system full-link monitoring method based on high-frequency index acquisition optimization, which comprises the following steps: monitoring the running state of an information management system in real time, dynamically adjusting the sampling frequency by means of a customized service key identification component and a comprehensive load prediction model, and performing real-time monitoring on the sampling frequency. Transmitting the target data to the edge computing node; a lightweight monitoring agent is deployed at an edge node, and a wavelet signal decomposition algorithm is adopted to extract features and distinguish data types; constructing an information management business knowledge graph and an entity-relation-business rule base, associating abnormal features, and generating an abnormal root cause report in combination with a time sequence prediction model and a knowledge constraint large language model; based on report and information service priorities, monitoring resources are dynamically allocated in the edge-cloud collaborative architecture, and related model parameters, service association rules and constraint weights are optimized according to operation and maintenance feedback. According to the invention, targeted monitoring requirements in the business peak period and efficient utilization of system resources can be met at the same time.

The invention provides an enterprise knowledge graph automatic construction and intelligent retrieval method, which comprises the following steps: collecting multi-source data from a heterogeneous enterprise information system, and carrying out data cleaning and standardization processing; on the basis of a comprehensive scoring mechanism of field similarity and behavior semantic vectors, entities from different systems are merged, and a standard entity set with a unique identifier is generated; based on the standard entity set, in combination with a scoring mechanism of a task-type relationship and a collaborative relationship, extracting a semantic relationship from a behavior record, and constructing an enterprise knowledge graph structure; extracting representative semantic paths from the knowledge graph structure, screening high-quality paths through a path scoring model, and organizing the high-quality paths into a structured path index set; and receiving a natural language query statement, encoding the natural language query statement into a semantic vector, matching the semantic vector with the path index set, executing query in the atlas in combination with an authority control mechanism, and returning a result.

A system can receive user input data that comprises an identification of a computer infrastructure component of a group of computer infrastructure components that are associated with a user account. The system can identify information about the group of computer infrastructure components based on the identification of the computer infrastructure component. The system can convert text of the user input data into a first numerical vector. The system can create a context of the user input data based on identifying a match between the first numerical vector and a second numerical vector of a group of numerical vectors, wherein the context corresponds to a natural-language version of the second numerical vector. The system can combine the context and the information about the group of computer infrastructure components into a combined context, and input the combined context and the user input data to a large language model to produce a result.

The invention provides a paper file information input method, system and device and a medium, and belongs to the technical field of file information processing. The method comprises the steps of collecting a paper file image, performing preprocessing in sequence to obtain a preprocessed image, and performing region segmentation on the preprocessed image by using a target detection algorithm to generate a region coordinate mapping table; generating a file template by using a predefined file template library according to the region coordinate mapping table; performing printing form recognition and handwritten form recognition on characters in the image by using a sequence generation model to generate a text sequence, and recognizing a table structure by using a two-dimensional convolutional network; according to the text sequence and the table structure data, a named entity recognition model is used for labeling field types, data formats are checked and corrected according to template rules, errors are corrected in combination with context semantic similarity, and structured data are generated; and mapping the structured data to an information system database table according to a template field mapping rule, and inputting the structured data into an information system.

The invention discloses a dynamic data docking method based on a rule engine, which comprises the following steps: S1, data source registration and automatic detection: a user inputs various heterogeneous data source information through a system console, and a system automatically detects the data source type, the data structure and the connection availability and generates an adaptive connection configuration file; according to the method, a dynamic data docking method with the rule engine supporting hot updating as the core is introduced, seamless integration and flexible conversion of multi-source heterogeneous data are achieved, and the problem of business interruption caused by code modification and service restarting due to rule change in a traditional scheme is thoroughly solved; through visual rule management, a unified data model and a closed-loop verification feedback mechanism, the development and maintenance cost of the system is remarkably reduced, and meanwhile, the flexibility, reliability and traceability of data processing and the continuous self-adaptive optimization capability of the system are greatly improved.

The invention relates to the technical field of pediatric medical treatment, and discloses a pediatric neonatal jaundice clinical phototherapy management system, which integrates illumination data in an equipment lamp box through a data integration module, extracts the illumination data acquired by the data integration module through a fusion analysis module, and fuses the operation duration of a lamp tube to obtain a phototherapy result. An equipment health state basic model is established, the current equipment health state is predicted through an equipment prediction module on the basis of the established health state basic model, a prediction result is fed back, a patient information system is connected through a personality support module, and basic physiotherapy data of a patient is acquired. And outputting recommended illumination intensity and recommended treatment time based on the basic physiotherapy data, and monitoring a plurality of pieces of monitoring information and feedback output results through a remote monitoring module. The system accurately solves the core problems of dynamic fluctuation of phototherapy intensity, calibration lag and lack of personalized adaptation, and finally achieves dual guarantee of phototherapy effect and safety.

The invention discloses an automatic auditing and checking system and method for substation operation safety. The system comprises an automatic data acquisition module, a data semantic fusion analysis module, a dynamic auditing rule generation module, a risk collaborative prediction module, an automatic information pushing module and a visual interaction configuration module. All the modules are connected through an intranet data interface and a system internal communication protocol, aiming at the prominent problems that the auditing process depends on manpower, the information system is split, the system semantics is difficult to understand, the risk identification is not comprehensive, the rule adaptability is poor, the response and push chain is broken and the like commonly existing in the existing substation operation auditing work. The invention provides an automatic auditing and checking system and method for substation operation safety, and aims to construct a full-process closed-loop intelligent auditing platform with semantic comprehension capability, multi-source data fusion capability, risk collaborative prediction capability and dynamic rule evolution capability.

The invention relates to the technical field of text processing, and provides a technical description text generation information system and method. The system comprises a core element extraction module and a hierarchical attention generation module. The core element extraction module comprises a supervised extraction path and an unsupervised extraction path parallel to the supervised extraction path, and is used for extracting a core element set from a text input by a user. And the hierarchical attention generation module is used for calling different attention mechanisms to generate the technical description text based on the core element set and the chapter type of the to-be-generated technical description text. According to the method, the generation efficiency of the technical description text can be remarkably improved while the structuralization and logicality of the generated content are ensured.

The invention discloses a tightening process abnormal fluctuation analysis and early warning method and system, and the method comprises the steps: collecting original torque and angle signals of a tightening process in real time, carrying out the time synchronization processing, and carrying out the abnormal value filtering and feature extraction, thereby obtaining a feature data set; then comparing and analyzing the feature data set and a pre-generated standard tightening curve, and performing anomaly judgment through a trained anomaly recognition model based on a comparison result to generate an anomaly recognition result; and finally, determining an early warning level according to an abnormal recognition result and outputting corresponding early warning information. The system correspondingly comprises a data acquisition module, a feature extraction module, an abnormity identification module and an early warning output module. According to the method and system, the dynamic time warping algorithm and the long-short-term memory network model are adopted, early-stage tiny abnormal fluctuation in the tightening process can be effectively recognized, multi-stage early warning and preventive quality control are achieved, and the quality control level and production efficiency of the tightening process are remarkably improved.

A method includes receiving acoustic signals from a user. The acoustic signals are transformed into data. The data are transmitted to a voice-to-text conversion and artificial intelligence system over a network. Information is received from the voice-to-text conversion and artificial intelligence system. The information was obtained from the data and the information is used to create a request to a hotel. A computer readable medium contains executable computer program instructions, which when executed by a data processing system, cause the data processing system to perform a process that includes; receiving acoustic signals from a user; transforming the acoustic signals into data; transmitting the data to a voice-to-text conversion and artificial intelligence system over a network; receiving information from the voice-to-text conversion and artificial intelligence system, wherein the information was obtained from the data; and using the information to create a request to a hotel through a hotel information system.

The invention discloses an urban water supply network satellite leakage detection method based on multi-source data fusion, and the method comprises the steps: S1, obtaining multi-source data, including a satellite remote sensing image, DMA partition measurement data, and Internet of Things sensor data; s2, preprocessing the multi-source data, including data cleaning, feature extraction and space-time registration; s3, constructing a multi-modal data fusion model, and carrying out feature fusion and leakage point recognition on the preprocessed data through a deep convolutional neural network; s4, performing leakage risk assessment in combination with a geographic information system and a dynamic hydraulic model, and generating a suspected leakage point list with priority ranking; and S5, performing iterative optimization on the model based on a ground checking result to form a closed-loop feedback mechanism.

The invention discloses a multi-modal rumor detection method fusing texts, images and social propagation structures, and belongs to the technical field of natural language processing, computer vision and causal reasoning. Specifically, the invention provides a unified causal inference framework, and hybrid deviation in multi-modal data is effectively stripped by integrating text anti-fact causal inference and an image dot product causal intervention mechanism. Under the framework, social propagation structure features are further fused, and a multi-head collaborative attention mechanism is adopted, so that deep alignment and semantic enhancement in cross-modal features are realized. Adversarial samples are generated through projection gradient descent for adversarial training, and model parameters are optimized in combination with anti-fact loss, so that the classification accuracy and generalization ability of the model are improved. According to the rumor detection method, a causal reasoning normal form is introduced into a rumor detection task, the effectiveness of an anti-fact and intervention mechanism in a complex information scene is verified, and a new theoretical support and method path are provided for constructing a credible multi-modal information system.

The invention belongs to the technical field of geospatial information systems, and particularly relates to a component-level catenary three-dimensional model lightweight three-dimensional tile conversion method, which comprises the following steps: S1, forming a component-level fine model data set with semantic annotations; s2, constructing a detail level division rule; s3, reconstructing a lightweight linear component model; s4, constructing a comprehensive evaluation function Q, deleting the body-shaped components of which the Q values are smaller than a preset threshold value, and retaining the body-shaped components of which the Q values are greater than or equal to the preset threshold value; s5, obtaining optimized body-shaped component model data; and S6, according to the detail level division rule in the S2, assembling and recombining the lightweight linear component model in the S3 and the optimized body-shaped component model data in the S5, generating a hierarchical component structure, converting each component into a three-dimensional instance model, and outputting a three-dimensional tile data structure. And efficient organization and visualization of the contact network BIM model in the GIS environment are realized.

The invention discloses a dynamic coupling modeling method and system for an electric power information physical system, and belongs to the technical field of electric power dispatching automation, and the method comprises the steps: analyzing an AGC control process business data flow, and constructing a workflow engine; performing node classification, generating an information node model and an information branch model of the information system, and constructing a rule engine; constructing an information system network matrix model based on the rule engine, and establishing a preset service strategy based on the information system network matrix model; constructing an information physical coupling model of the AGC control process; and according to the AGC actual service, loading a preset service strategy established by the information system network matrix model based on the synergistic effect of the workflow engine and the rule engine, and updating the information physical coupling model. According to the method, a basic model is provided for cross-level closed-loop simulation verification in the AGC process, the problems of unclear information physical dynamic coupling mechanism, insufficient service logic adaptive mapping and model iteration self-updating are solved, and a guarantee is provided for safe and stable operation of a large power grid.

The invention discloses an environment perception and command control intelligent deduction platform based on bionic unmanned equipment, and relates to the field of intelligent deduction, and the platform comprises the steps: collecting environment data through a multi-mode sensor, encrypting the environment data through an anti-interference communication relay module, and transmitting the encrypted environment data to a central control platform; the data fusion preprocessing module is used for processing multi-source data and outputting a structured data stream, and the environment intelligent modeling module is combined with a geographic information system to construct a three-dimensional dynamic environment model; an intelligent deduction module carries out multi-scene deduction based on the model, and a self-adaptive control strategy generation module converts a decision tree into an anti-disturbance control sequence; and the man-machine collaborative decision-making module fuses operator intervention to generate a final instruction, and the instruction distribution and equipment collaborative control module issues the instruction to the bionic unmanned equipment to realize intelligent collaborative control. The method has the advantages that bionic perception, anti-interference communication and intelligent deduction are integrated, efficient cooperation and adaptive control of unmanned equipment in a complex environment are achieved, and the intelligence and robustness of task execution are remarkably improved.

The invention discloses an intelligent agent platform and information system integration compatible method and equipment, belongs to the technical field of digital transformation, and aims to overcome the defects of high cost, long development period, difficulty in maintenance and the like of an existing intelligent agent platform and information system integration scheme. And dynamic upgrading of an enterprise system and access of a new system are difficult to adapt. The method comprises the following steps: constructing dynamic protocol conversion middleware supporting multiple protocols, and converting heterogeneous protocol data through the dynamic protocol conversion middleware to obtain standardized data; performing format conversion on the standardized data through a hierarchical data converter to obtain readable data; respectively transmitting the high-frequency calling data and the low-frequency calling data to an intelligent agent platform through a hybrid communication bus; wherein enterprise sensitive data in the readable data is transmitted to the intelligent agent platform in a token form after being subjected to desensitization operation and / or encryption operation.

Systems and methods for selection of client connection type in a virtual meeting based on stored configuration information. In response to a request of a first participant of a virtual meeting platform to join a virtual meeting, a configuration data structure associated with the virtual meeting is accessed. The configuration data structure identifies roles for participants of the virtual meeting. A first role associated with the first participant within the virtual meeting is identified using the configuration data structure. One or more client connection types are assigned to the first participant based on the first role. The first participant is allowed to join the virtual meeting using one of the one or more client connection types.

The invention discloses a sheep abnormal behavior intelligent monitoring method and system based on multi-source data fusion and deep learning, and the method comprises the steps: collecting the multi-source data, such as the motion trail, limb joint angle, body temperature, sound and environmental parameters, of a sheep through multi-type sensing equipment, and carrying out the time-space alignment to form a feature matrix; encoding and reconstructing the feature matrix by using a variational auto-encoder to generate a reconstructed feature matrix, and calculating errors of the two feature matrixes to form an error sequence; and inputting the error sequence into a local abnormal factor analysis model to obtain an abnormal factor sequence, judging an abnormal behavior through a threshold value, and outputting related information. The system comprises a multi-dimensional parameter acquisition unit, a spatial-temporal feature fusion unit, a feature reconstruction unit, an error sequence generation unit, an abnormal factor analysis unit and an abnormal judgment output unit. The method and the system realize multi-source data fusion, improve anomaly identification accuracy, adapt to dynamic changes and are suitable for large-scale breeding.

Disclosed is a mutually generative artificial intelligence system based on multi-dimensional spatiotemporal information vector graphics, relating to the field of artificial intelligence and engineering applications. Based on a geographic information system (GIS) or a computer-aided design (CAD) platform and a data source, a multi-dimensional vector spatiotemporal large model terminal, a multi-dimensional spatiotemporal information processing agent terminal, and an intelligent information system application terminal are constructed. For multi-dimensional spatiotemporal data such as two-dimensional and three-dimensional vectors and temporal states, a multimodal spatiotemporal large model having an understanding capacity for an engineering professional knowledge system, a data processing flow, multi-dimensional vector graphics, and thematic graphics-text documents is pre-trained to achieve the mutual expression and generation of engineering multi-dimensional vector graphics and thematic graphics-text documents and to form an intelligent engineering graphic data processing application.