138 results about "Data view" patented technology

The invention belongs to the technical field of office park electric load prediction, and relates to an office park electric load prediction and scheduling method for a novel electric power system. The method comprises the steps that S1, multi-source data fusion and panoramic view construction are carried out, historical load data of a park are collected, and park operation data, meteorological data and a special event calendar are obtained; s2, data preprocessing and feature directional extraction; s3, building and cooperating short-term, medium-term and long-term prediction models on the basis of multi-time scale prediction of model cooperation to form a hierarchical prediction system; s4, optimizing and evaluating a prediction result, and performing uncertainty evaluation on the prediction result in the step S3; and S5, generating and executing a hierarchical scheduling instruction based on hierarchical scheduling decision and execution of multi-objective optimization. According to the method, the problem of full-chain link splitting is solved, panoramic data view, collaborative prediction model, quantitative risk assessment and multi-target optimization scheduling are realized, prediction accuracy and scheduling flexibility are improved, and active participation in energy management of the office park is supported.

The invention discloses a financial abnormal event analysis method, electronic equipment, a medium and a product. The method comprises the steps of obtaining at least one financial clue event, and performing structured element extraction and standardization processing on each financial clue event to obtain a standardized event behavior sequence; performing semantic feature and behavior pattern analysis based on the normalized event behavior sequence, performing event reasoning rule recall in combination with a pre-constructed event reasoning library, and determining a recalled rule set; generating an abnormal event analysis execution plan based on at least one inference rule in the rule set; querying original data in the data system according to an inference rule included in the abnormal event analysis execution plan, generating a data view, executing the abnormal event analysis execution plan based on the data view, and generating an inference execution result set and execution path information; and an event reasoning analysis result is generated according to the reasoning execution result set and the execution path information, and the problems of complex abnormal event analysis modeling, low interpretability and the like are solved.

The invention discloses a big data measurement asset supply and demand matching and inventory optimization method, and relates to the technical field of big data processing and supply chain management. The method comprises the following steps: segmenting supply chain asset data through a hash function according to multi-dimensional attributes to generate a data fragment set, and constructing a global index tree according to the data fragment set; and monitoring the load state of the leaf nodes of the global index tree in real time, and migrating and verifying data during unbalance. And querying the global index tree, positioning fragment data associated with the query request from the uniformly distributed leaf nodes, generating a preliminary matching asset set, calculating the matching degree of each asset and the query request, and generating a resource allocation result. And updating the global index tree, and generating the latest data view representation. And adjusting the attribute weight coefficient of each dimension in the hash function, and generating optimized storage layout configuration. Irrelevant data are filtered through a neighbor algorithm, and a final matching result set is generated. Balanced storage, efficient query and accurate matching of asset data are realized, and the overall response speed and the resource utilization rate are improved.

The embodiment of the invention discloses an intelligent number asking method and system based on dynamic feedback, a storage medium and electronic equipment. The method comprises the steps that a subject domain and a semantic model are constructed, a data view is established, data mapping is configured, and a natural language problem and a standardized index are analyzed; generating an SQL (Structured Query Language) logical expression based on the Few-shot example and the large model, and carrying out semantic correction on the SQL logical expression; sQL query is executed, dynamic feedback storage is carried out based on an execution result, and SQL generation parameters are updated by utilizing a self-adaptive learning mechanism. According to the method, through semantic modeling and data mapping, precise alignment of a natural language and a database structure is achieved; few-shot examples and large model generation are combined with semantic correction rules, so that the accuracy and stability of SQL generation are improved; and a continuously optimized intelligent number-asking closed loop is constructed by executing a feedback and adaptive learning mechanism, so that the self-learning and evolution capabilities of the system are improved.

The invention relates to the technical field of software, and discloses a nursing shift change system based on homologous heterogeneous data fusion and a large language model, and the system comprises a shift change generation module which comprises a first generation unit and a second generation unit, calling a large language model to generate global summary information of nursing shift change; and the second generation unit is used for calling a large language model to generate corresponding detailed handover information only based on the original data of the key event. And the report synthesis module is used for integrating the global summary information and the detailed handover information according to a preset structure to generate a nursing handover report. According to the method, the panoramic data view of the patient is constructed based on the unified time axis, so that structured data and unstructured data which are originally dispersed in different systems can be organized and called in the same semantic space, and a consistent data basis is provided for subsequent data analysis and processing.

The invention relates to a data-in-channel-based cross-source data joint query method, which comprises the following steps of: S1, constructing a data-in-channel access strategy model, and automatically generating a most suitable access mode; s2, constructing a power data knowledge graph, and analyzing a dependency relationship, a traceability path and a blood relationship among the data by using a graph neural network; s3, seamless access is achieved through natural language understanding, natural language query translation is adopted, and the natural language query of the user is converted into a corresponding SQL statement; s4, according to the SQL statements, similarity is calculated through the embedded vectors, user problems and data models are matched, and according to historical query modes and service requirements, a virtual data view is generated; s5, based on the generated virtual data view, sensitive information fields possibly contained in the data set are recognized through a natural language model and regular pattern recognition, and automatic labeling and classification are carried out. According to the method, the technical threshold of data fusion and sharing is remarkably reduced, and the intelligence of a data platform system in the power industry is improved.

The invention discloses a cross-platform teaching tool data collaboration and personalized resource recommendation system based on an MCP protocol, and belongs to the technical field of education. According to the system, a multi-platform teaching tool is in unified butt joint through the MCP protocol adaptation layer, and the problem of data splitting is solved; the data co-processing layer cleans and fuses multi-tool data, generates a teacher / student / parent data view and stores an evidence through a block chain; the personalized recommendation engine generates role-based resource recommendation based on a teaching knowledge graph and multi-dimensional behavior analysis; the user interaction layer supports multi-terminal access, and the data security module guarantees compliance. According to the system, the cross-platform data collaboration efficiency is improved by 70% or above, the resource recommendation matching degree reaches 92%, the system is suitable for K12 education, higher education and vocational education scenes, teaching tool data barriers are effectively broken through, and the teaching data utilization rate and the resource recommendation accuracy are improved.

The invention discloses an enterprise digital management system based on multi-source data fusion, and the system comprises a data collection module which is used for constructing a multi-source data view from internal and external data sources of an enterprise; the embedding mapping module is used for generating a feature domain embedding vector set; the improved extremely deep factorization machine model module is used for feature extraction and explicit high-order interactive modeling and outputting a basic matching score; the triple generation module is used for constructing a positive and negative sample triple and calculating a business importance coefficient and an exposure probability; the Bayesian personalized sorting module is used for constructing weighted sorting loss and updating model parameters; and the online recommendation module is used for calculating matching scores of the candidate schemes and sorting and outputting a recommendation management list. According to the method, accurate and intelligent recommendation and sorting decision of candidate schemes in an enterprise management scene are realized by improving an extremely deep factorization machine model and Bayesian personalized sorting.

The application relates to the computer technical field, in particular to a data display method and device, electronic equipment and storage medium, to improve the data viewing efficiency. The method comprises the following steps: presenting a video display interface containing an access record video of a first object and a data display control; in response to a selection operation of a second object on a target video frame in the access record video, displaying the target video frame in the video display interface; and in response to a trigger operation on the data display control, drawing a corresponding heat map based on an operation behavior data set of the first object in a target operation page displayed by the target video frame, and superimposing and displaying the heat map on the target operation page. In the application, the second object can freely select the target video frame to generate the heat map according to the demand, which has high flexibility, and a large number of page snapshots do not need to be saved to meet the object demand, so that the data viewing efficiency is improved and the storage space occupation is reduced.

The application belongs to the technical field of intelligent security and protection home, and relates to a smart floor system capable of identifying falling behaviors, which comprises a smart pressure sensing floor, a data acquisition system and an upper computer, the smart pressure sensing floor is a composite structure of a solid floor and a flexible sensing fabric, the flexible sensing fabric contains 40 electrodes and 40*40 array distributed sensors, and a piezoresistive sensing layer is constructed by a graphene-carbon black mixed filler to form a conductive network; the data acquisition system collects signals through FPC flat cable, transmits data to the upper computer through a sensor router and a public network router; the upper computer adopts a "cloud-edge-end" architecture, carries a machine learning identification algorithm, can accurately identify falling and intrusion behaviors, the falling identification accuracy is more than 98%, and the response time is less than or equal to 1 second; the terminal side is associated with a cloud program to realize alarm pushing and data viewing functions. The disclosed system simultaneously integrates two core functions of old people falling monitoring and home safety protection, and meets the diversified needs of users living alone.

This disclosure provides a method and apparatus for processing hydraulic models. The method includes: acquiring model data from multiple hydraulic models; receiving a data viewing request and determining a matching target hydraulic model among the various hydraulic models based on target constraints in the request; the target constraints include rainfall information and a first rainfall duration, wherein the rainfall information is determined based on a rainfall alarm received by the client, and the first rainfall duration is set by the client; determining the target model data of the target hydraulic model and sending it to the client, so that the client renders a data display page of the target hydraulic model based on the target model data; the page includes display information of a target flood inundation event, which is simulated by the target hydraulic model, and the duration of the target flood inundation event in the display information matches the duration of the first rainfall. This embodiment can improve the accuracy of flood risk prediction using hydraulic models.

This invention discloses a pallet rental data management method, system, intelligent device, and storage medium. The method includes: obtaining the user identifier of the current user and the database identifier of the currently accessed database; obtaining a customer number list string based on the user identifier and database identifier; saving the customer number list string to a session variable; establishing a custom function to obtain the customer number list string; splitting the customer number list string into a row-based list view; establishing a data view for the relevant data tables in the currently accessed database; associating the list view with the data view to obtain the associated view; setting the relevant data tables to write-only; obtaining the query information input by the current user; retrieving result data from the associated view based on the query information; and providing the result data back to the current user. This invention ensures effective isolation of data in the shared pallet rental system and guarantees the confidentiality of user data.

The application provides a clinical data asset management method and system based on data intelligent anonymization, and the method comprises the following steps: collecting, cleaning and integrating medical clinical data from multiple source heterogeneous medical information systems, and constructing a unified database providing data view function; according to the characteristics and use scenarios of the medical clinical data, the best anonymization strategy is adaptively selected to anonymize the medical clinical data, and the privacy protection and data availability are balanced; the privacy risk of the anonymized data is evaluated, the possibility of data re-identification is quantified by simulating the behavior of an attacker, and a scientific basis is provided for privacy protection strategy adjustment; a data asset directory is established and managed, medical data is regarded as important assets for classification, evaluation and management, and the discoverability and availability of data assets are realized. The application improves the integrity, accuracy and consistency of data, realizes all-round privacy protection, and maximizes the availability and analysis value of data.

The invention discloses a health data linkage management system for pregnant and lying-in women in a large perinatal period, and belongs to the technical field of intelligent data management. The system comprises a multi-source heterogeneous data access and standardization gateway which is used for connecting household equipment and a hospital system and standardizing original data through a deep cleaning engine; a data fusion and association unit of the central data processing server fuses multi-source data according to a time sequence by relying on a gestational week management unit, and a multi-modal health analysis engine is combined with a clinical rule and a machine learning model to carry out early warning, risk prediction and personalized analysis; and the multi-terminal interaction platform provides a fusion data view and a closed-loop management tool based on role permission. According to the invention, equipment and hospital information islands are broken through, and through high-quality data management and'rule + AI 'fusion analysis, accurate and foresight management and efficient cooperation of the full-cycle health state of pregnant and lying-in women are realized.

The present application relates to the field of data analysis, and discloses a logistics operation data intelligent analysis method, device, equipment and storage medium, which is used for analyzing and abnormally warning logistics operation data. The method comprises the following steps: acquiring logistics operation data in real time, and performing stream processing and standardization processing on the logistics operation data to obtain a real-time data view; based on the real-time data view, an real-time index system covering multi-dimensional features of network operation is constructed; based on the real-time index system, a clustering algorithm and a time series analysis method are used to dynamically grade and evaluate the operation state of each network point to obtain an abnormal grading result; based on the real-time index system and the abnormal grading result, a pre-trained time series prediction model is used to predict potential abnormalities of each network point to obtain a prediction result; and based on the prediction result and the abnormal grading result, a multi-dimensional visual analysis report is generated.

The invention belongs to the technical field of temperature and humidity control of power equipment, and particularly relates to a 10kV ring main unit self-adaptive condensation eliminating device and a humidity control method. The device comprises five modules: a power supply module uses solar energy and a control PT to control dual power supply to guarantee continuous power supply, a state detection module collects temperature, humidity and safety signals in a cabinet, a dehumidification execution module processes and discharges condensed water, a control module overall plans dehumidification start and stop and power supply switching, and a remote monitoring module supports data viewing and abnormity alarm. The control method comprises the following five steps: firstly, collecting data according to a dynamic sampling period, setting control for 5 minutes in rainfall or strong wind, calculating according to information entropy in other conditions, and filtering the data; combining historical data of federal learning processing, and using a control LSTM to control and an attention model to judge the condensation risk; then switching power supply, starting and stopping dehumidification and combining the aging state of the element; then carrying out transfer learning to judge result transmission data; and finally, according to a cabinet body structure coefficient adjustment strategy, condensation elimination and monitoring are realized, and energy consumption and standard reaching time are optimized.

The present application relates to the field of medical education management, and more particularly to an intelligent management method and system applied to a medical education platform, comprising the following steps: collecting multi-source data related to medical education, forming a structured initial data set through data cleaning processing; based on the structured initial data set, constructing a four-dimensional intelligent adaptive model, establishing a mapping relationship, generating a personalized permission configuration result and a data view; collecting relevant data of students, departments and rotation templates, realizing intelligent linkage of rotation scheduling, teaching activities and evaluation and examination through a fusion algorithm, and outputting business data; generating a personalized learning resource pushing result through feature extraction and model training; extracting student graduation related data, checking the graduation conditions and outputting the compliance status result. The present application realizes intelligent linkage of medical education business and data closed loop through the construction of a four-dimensional intelligent adaptive model, the fusion of multi-algorithms and the processing of whole-process data.

The invention discloses a charging equipment data management method based on an electric red-Internet-of-Things operating system, relates to the technical field of charging equipment data management, and automatically integrates structured and unstructured data such as charging quantity and equipment logs through metadata acquisition capability of the electric red-Internet-of-Things operating system. The service context such as user identity and scheduling instruction is associated, a unified data view covering space-time dimension and service semantics is constructed, cross-system linkage scenes such as charging habit analysis and load prediction are supported, and a data association barrier is broken; a dynamic value quantification model is combined, a data utility value is calculated in real time, a threshold response is triggered, an engine can autonomously schedule operation sequences such as encryption and migration, unattended strategy adjustment is achieved, and emergency requirements such as compliance events are rapidly coped with; a flexible operation combination generated through strategy algebra compiling can adapt to complex scenes such as fault processing, auditing and checking and load regulation and control, and the intelligent level and the service response capability of charging network data management are remarkably improved.

The embodiment of the invention provides a multi-source data processing method and device, equipment, a storage medium and a program product, and relates to the field of big data and financial science and technology. The method comprises the following steps: acquiring multi-source heterogeneous data, wherein the multi-source heterogeneous data comprises a set of data from different systems or formats; based on the knowledge graph, performing entity recognition on the multi-source heterogeneous data to obtain entities in the multi-source heterogeneous data; performing relation mapping on the entities to obtain semantic alignment data; and through context reasoning and a dynamic updating mechanism, when the business rule changes, optimizing the semantic alignment data to obtain a target data view. According to the method, the problem of semantic islands of cross-system data is solved, semantic unification and format standardization of multi-source data are realized, a high-quality and traceable unified data view is provided for subsequent data processing, and data fusion efficiency and business suitability are remarkably improved.

The invention is suitable for the technical field of intelligent manufacturing, and discloses an intelligent manufacturing multi-source data fusion intelligent intelligence service system architecture method, system and device based on multi-model fusion, and a medium, and the method comprises the steps: standardizing intelligent manufacturing multi-source data; processing the standardized multi-source data and constructing a unified data view by taking the key business identifier as a first association key; based on the unified data view, adopting a first model to generate sales volume trend prediction information and adopting a second model to generate personalized product recommendation information; and in response to the acquisition of the sales volume trend prediction information and the personalized product recommendation information, the business application executes a decision and feedback operation. According to the invention, through a plurality of parallel deep learning models, information oriented to different businesses is generated in real time, the problem of data islands in intelligent manufacturing is effectively solved, and deep fusion and real-time intelligent service of multi-source data are realized.

The application relates to the technical field of data noise reduction, and discloses a security alarm noise reduction method and system based on a data weaving technology, which comprises the following steps: based on a data weaving architecture, a unified logical data view is constructed; an AI-driven data intelligent agent component system is deployed, API and new data sources that change automatically are recognized and adapted, metadata, threat intelligence and infrastructure operation state information are fused; an attack chain panoramic graph and a behavior causal chain model are constructed; a semantic noise reduction algorithm, time series clustering analysis and a confidence score mechanism are used to remove duplicate alarms, identify false alarms and filter low-risk events for security alarms; and alarm deduplication, priority adjustment and linkage disposal strategy generation are carried out. The application solves the problems of alarm flooding, high false alarm rate and low processing efficiency in the existing security alarm system.

The invention relates to the field of medical education management, in particular to an intelligent management method and system applied to a medical education platform, and the method comprises the following steps: collecting multi-source data related to medical education, and forming a structured initialization data set through data cleaning processing; based on the structured initialization data set, constructing a four-dimensional intelligent adaptation model, establishing a mapping relation, and generating a personalized permission configuration result and a data view; relevant data of students, departments and a rotation template are collected, intelligent linkage of rotation shift arrangement, teaching activities and assessment evaluation is achieved through a fusion algorithm, and service data are output; generating a personalized learning resource pushing result through feature extraction and model training; and extracting related data of trainees' employment, verifying employment conditions and outputting a standard state result. According to the invention, by constructing the four-dimensional intelligent adaptation model and fusing multi-algorithm and full-process data processing, intelligent linkage and data closed loop of medical education services are realized.

The application discloses a game efficiency evaluation method and device based on a dynamic index tree and an operator library, and the method comprises the following steps: firstly, acquiring game scene configuration information, a multi-source data information set and index construction request information; then, performing analysis processing on the index construction request information, selecting basic indexes from an index library and generating target index system information; next, pre-processing the multi-source data information set, calling pre-processing operators in the operator library to form standardized data view information; finally, performing calculation and visualization processing on the target index system information and the standardized data view information, generating a directed acyclic calculation task graph by analyzing index dependency, scheduling calculation operators in the operator library to perform calculation, and automatically matching a visualization template according to an index type to perform rendering, so as to obtain target game efficiency evaluation result information.

The invention relates to the technical field of data mining, in particular to a group construction evaluation method and system based on data mining, and the method comprises the following steps: constructing a panoramic data view; classifying each piece of system data in the panoramic data view as a full-amount data set, and correcting abnormal data of the full-amount data set; constructing a plurality of member data subsets corresponding to each group member, preprocessing the member data subsets and a full-amount data set; analyzing a total data set with relevance, and receiving a plurality of member data subsets after duplicate removal; calculating a variable coefficient of the full-amount data set where the abnormal data is located, and analyzing whether the abnormal data is supplemented according to the full-amount data set and the member data subsets or not; key data weights are distributed to the full data set, and member scores are calculated to output group construction evaluation; and when the key data weights are distributed, quantifying the key data weights corresponding to the plurality of full-amount data sets through variable coefficients, and adjusting member scores according to the member data subsets corresponding to each group member in the full-amount data sets.

The application discloses a kind of active NFC-based touchless material transportation data acquisition and protection system, it is related to logistics monitoring equipment technical field, including monitoring host module, active NFC module and waterproof and installation structure module;Wherein, monitoring host module includes the transport monitoring host (100) being set in the shell inside, acceleration sensor module (101), storage module (104) and power module (105) are integrated in transport monitoring host (100) micro-control unit MCU (102), monitoring host module is used to collect vibration, impact and inclination data in the process of material transportation and the data is locally stored and managed, active NFC module is integrated in the inside of transport monitoring host in the application and cooperates with wave-transparent waterproof structure, task creation, equipment automatic identification, touchless firmware upgrade, real-time data viewing and historical data export are all transferred to mobile phone NFC radio frequency link, under the condition of maintaining IP67 waterproof level, touchless interaction of whole process of material transportation is realized.

The invention discloses a data security management method, device and equipment for power grid infrastructure and a medium, and the method comprises the steps: obtaining a user authority level of a user in response to a viewing instruction of the user for power grid infrastructure data; according to the first power grid infrastructure data checked by the user, the encryption level of the first power grid infrastructure data is determined; based on the user permission level and the encryption level, judging whether the user meets a viewing condition; if the user conforms to the viewing condition, screening first power grid infrastructure data conforming to the user permission level and the encryption level; and if the user does not meet the viewing condition, screening second power grid infrastructure data and sending the second power grid infrastructure data to the user based on the user permission level and the first power grid infrastructure data. According to the method, the security of the power grid infrastructure data can be effectively improved, so that the data is prevented from being leaked and tampered.

This invention relates to a multi-source data fusion management method and system for medical record information, comprising the following steps: collecting data from the electronic medical record system, medical imaging workstation, and laboratory information system of a medical institution to obtain an original medical record dataset; performing semantic mapping and concept association on the original medical record dataset based on a preset medical ontology knowledge graph to obtain a semantically associated medical record information network; performing dynamic temporal feature analysis on the semantically associated medical record information network through a temporal feature extractor to obtain a temporal medical record feature sequence; and performing heterogeneous data fusion on the temporal medical record feature sequence to obtain a unified medical record data view. This invention solves the technical problem that existing medical record management methods often ignore the semantic relationships between data, which limits the ability to deeply understand and mine medical record information.