239 results about "Data dynamics" patented technology

The application discloses a fan operation and maintenance data dynamic encryption method for multiple regions and multiple clients, belongs to the technical field of industrial data security and intelligent terminal protection, and is a method for differentiating and dynamically encrypting and protecting operation and maintenance data stored locally by a fan AI assistant client according to the region to which a client belongs, a permission level and data sensitive attributes, specifically comprising the following steps: according to a client region compliance requirement, a data sensitive level and a terminal identity, dynamically matching encryption parameters through a built-in strategy matrix, and completing fan operation and maintenance data protection in the whole encryption life cycle locally on the client, so that the problems of the fact that existing static encryption cannot meet the differentiated security requirements of multiple regions, key risks are concentrated, and resources are wasted are solved.

This invention discloses a low-cost, low-speed USB circuit control method. It collects bus transmission timing signals, port voltage fluctuation data, and peripheral access status information through an embedded USB fault diagnosis platform to construct a multi-dimensional operational dataset. Based on a differential timing coupling mapping model, it mines the nonlinear coupling relationship of timing signals. A low-speed bus power consumption balancing model regulates power distribution, and a hardware timing error correction algorithm compensates for timing deviations. A low-cost control module converts the corrected parameters into hardware drive signals to achieve data transmission and peripheral control. The fault diagnosis platform monitors operational feedback data in real time and dynamically adjusts model parameters and control strategies. This method eliminates the need for high-cost dedicated chips and solves the problems of accumulated timing deviations and uneven power distribution in traditional methods through multi-model collaboration and closed-loop control. It reduces hardware costs while improving circuit control accuracy, stability, and operational efficiency.

This invention relates to the field of text processing technology and discloses a dynamic template generation system for test data of mobile maintenance of pumped storage power stations. The system includes: generating process activity degrees; dividing into stages; combining and generating stage feature vectors; generating a mask matrix; generating a set of patterns and stage grouping; constructing a two-dimensional rectangular grid and row mapping rules; generating a semantic dictionary; and generating acquisition results. This invention avoids structural redundancy caused by mechanism-selective column cluster holes by dynamically generating a two-dimensional rectangular grid template without complex topology. The strong binding between the globally unique primary key and the semantic dictionary ensures that semantic anchors remain stable during cross-platform conversion, preventing the loss of data physical meaning due to layout reflow. Simultaneously, the system can flexibly adapt to different test conditions and unit types, reducing manual template adjustments and providing convenient data acquisition support for mobile maintenance of pumped storage power stations, improving the standardization and efficiency of test data acquisition.

The application provides an intelligent parameterized UI generation system and method suitable for professional analysis software, receives UI requirements in the form of natural language or pictures through a user interaction layer, analyzes the requirements by an AI intelligent processing layer, and automatically generates an initial configuration file containing components, styles and logic in combination with a domain knowledge base and a reference style. A user can adjust and analyze the configuration file through a configuration editing and analyzing layer. A parameterized UI generation layer dynamically constructs UI components with tree hierarchical relationships based on the analyzed structured data, automatically configures interaction logic, data binding and professional field processing, realizes two-way synchronization of GUI and backend data, and finally outputs an interactive interface by a UI rendering layer. The application changes highly customized and fragmented UI development into an automated and standardized generation process, greatly improves development efficiency, guarantees the consistency of interface style and operation logic, significantly reduces maintenance cost, and enhances the flexibility of software function expansion.

The application provides an emotion perception-based Internet of Things information technology customer service method and system, and relates to the technical field of information technology services.The method comprises the following steps: obtaining real-time message data of a user and a customer service, and transmitting the data to a cloud server in real time through an Internet of Things platform; performing text analysis on the obtained real-time message data, and analyzing the current emotional state of the user through an emotion analysis method; analyzing the intention of the user according to the real-time message data, and generating reply content through a reply database according to the current emotional state of the user; continuously monitoring the interaction data between the user and the customer service, and dynamically adjusting the reply content.The application can analyze the emotional state of the user through emotion perception technology, thereby better understanding the demand and emotional state of the user, adjusting the reply content according to the emotional state of the user, and providing more personalized, warm and considerate services that are closer to the psychological demand of the user.

This invention relates to the field of airspace management technology, specifically disclosing a method and system for dynamically updating airport airspace obstacle data. The method includes: acquiring regional benchmark data based on a first acquisition precision under standard operating conditions to construct a benchmark regional model; acquiring real-time regional data periodically based on a second acquisition precision under real-time operating conditions to construct a real-time regional model with time labels; identifying the real-time regional model based on an adaptive detection parameter set, locating abnormal candidate areas, and simultaneously locating abnormal obstacles; marking the location results, and visually displaying the real-time regional model. This invention acquires relevant airport information through an acquisition device with data transmission capabilities, performs 3D modeling of the airport, and, combined with a pre-acquired standard model, quickly determines abnormal areas and objects at different times, thus providing intuitive feedback to management personnel. The method boasts extremely high identification efficiency and readability.

The application provides a kind of man-machine interaction identity intelligent identification method and system based on multi-modal perception, it is related to man-machine interaction technical field, first capture the behavior signal hierarchy sequence of interactive subject in man-machine interaction, trigger multi-dimensional perception feature derivation transmission generation feature derivation transmission unit, the feature derivation transmission unit contains the derivation and transmission relationship data of physiological, behavior mode, response feedback and the like feature, then according to progressive order unit chain is linked to form feature derivation transmission time sequence chain, record feature dynamic evolution track, then call preset identity benchmark chain library, combine scene parameter and historical data dynamically update generation scene adaptation benchmark chain, then extract cross-dimension core matching feature, with dynamic weight distribution strategy bidirectional track alignment, finally based on alignment result generation contains identity attribution and the like information of identity recognition conclusion, the method improves identity recognition accuracy, adaptability and intelligent level.

The application discloses a kind of based on blockchain's pedigree data dynamic permission access control system and method, rely on attribute-based access control paradigm, and combine pedigree data access constraint to carry out dynamic access control.First, user sends access request to policy decision point;Decision point according to the policy loaded from policy management point, request relevant information to blockchain, and call user historical behavior verification module based on pedigree data, the legality of current access request is verified using dependency relationship and pedigree data graph.System administrator records access request and verification result to blockchain, to support the fast verification of same query, reduce query overhead.In addition, the system passes access information such as query user, time, result, operation content to management node, for subsequent user access tracking and management.The method uses the anonymity and non-tamperability of blockchain, provides strong evidence for user supervision, realizes efficient management and reasoning to source information.

This application relates to the field of data security protection technology, specifically a dynamic data protection method based on intelligent classification and risk adaptation. The method includes: acquiring the data flow chain, recording the data flow relationship between the source Topic, target Topic, and processing nodes, and generating a link identifier; performing field parsing and two-level sensitivity identification on the input data to obtain the field sensitivity level and generate an initial residual risk vector at the field level; calculating the effective residual risk at the field level node by node during the data flow process and aggregating it to form a data risk label; determining policy entries and target processing operators based on the data risk label, path length, node processing type, and local link summary characteristics; and performing at least one operation on the target field: character replacement, interval truncation, tokenization, and envelope encryption. This method enables dynamic risk characterization and adaptive protection during the data flow process.

This invention discloses an urban land use classification method based on the fusion of multi-source data and deep learning, comprising: Step 1: Constructing a spatiotemporal map using Poisson disk sampling and graph neural networks, integrating the spatiotemporal heterogeneity of multi-source data, and dynamically adjusting weights using an attention mechanism; Step 2: Extracting static features from remote sensing and DEM using Swin Transformer, processing dynamic features from social media and mobile phone signaling using LSTM, fusing static and dynamic features through cross-modal attention, and optimizing data matching degree based on Grad-CAM++; Step 3: Combining the person-to-land flow of mobile phone signaling with the spatial correlation of social media activities, predicting trends using LSTM and embedding ecological indicator constraints; Step 4: Constructing a cross-departmental data sharing platform, collaboratively optimizing planning through a unified indicator system, and dynamically adjusting parameters using social media to mine public demands and POI data; Step 5: Introducing ecological footprint and carbon emission indicators to assess sustainability, establishing a monthly update mechanism, and dynamically calibrating model parameters through real-time data streams.

The application discloses an API data interaction processing method of a cake electronic coupon API docking system, and relates to the technical field of API data interaction processing. The method comprises the following steps: dynamically evaluating and determining the initial monitoring frequency of various electronic coupons based on the key performance parameters of the various electronic coupons in the cake electronic coupon API docking system; obtaining the monitoring frequency of the various electronic coupons by dynamically adjusting the initial monitoring frequency based on the user behavior data of the various electronic coupons; receiving an electronic coupon state update request, and dynamically configuring and optimizing the concurrent competition intensity of the master database corresponding to the electronic coupon state update request; after the dynamic configuration and optimization are completed, performing electronic coupon state updating, and dynamically updating and verifying the electronic coupon states in the master database and the slave database after the electronic coupon state updating, so that the lock competition pressure at the database level is effectively relieved, and the overall processing efficiency of the electronic coupon state update request is significantly improved in a high-concurrency business scenario.

The present application relates to the field of fire-fighting equipment safety technology, and more particularly to a method for intelligent anti-freezing protection and detection of outdoor fire-fighting pipe network in high-cold regions, which comprises four steps: S1, collecting multi-dimensional state data of key nodes of the pipe network in real time through a distributed sensor network; S2, inputting the data into a pre-trained model, fusing environment prediction and pipe network operation history data, dynamically calculating a risk coefficient and generating a graded early warning; S3, triggering a matched adaptive anti-freezing intervention strategy according to the risk level, starting microcirculation or low-power preheating at low risk, adding degradable anti-freezing fluid and increasing electric heat tracing power at medium and high risk, and emptying residual water in the end pipe at high risk; and S4, collecting data after the intervention to verify the effect, and feeding back the results and intervention instructions to the model to realize continuous optimization. The present application solves the anti-freezing pain point of the pipe network in high-cold regions, realizes efficient and energy-saving anti-freezing through dynamic grading intervention, and guarantees the integrity and availability of the pipe network under extreme cold.

This invention relates to the field of content generation technology, and particularly to a method, apparatus, device, and storage medium for generating interactive content in museums. The method parses multimodal information to obtain scene recognition information, matches it with a spatial semantic map to obtain exhibit categories, dynamically updates interest preference vectors based on exhibit categories and acquired multimodal behavioral data to generate dynamic visitor profiles, generates multimodal guided tour content through association reasoning based on exhibit categories, and obtains a sharing index based on multimodal behavioral data and dynamic visitor profiles using a sharing willingness assessment model. If the index exceeds a sharing threshold, materials are selected to generate content to be shared. This method solves the problems of fragmented interactive experience and inefficient sharing generation in existing guided tour modes, reduces the manpower and content operation costs of museum guides, provides technical support for upgrading the museum visitor experience and efficiently disseminating culture, and is applicable to intelligent guided tours and interactive content generation in various cultural and museum venues.

This application relates to a method, apparatus, device, and computer-readable medium for dynamic garbage data recycling. The method includes: collecting operating parameters of a distributed object storage cluster and submitting these parameters to an analysis cluster; constructing dynamic load profiles of multiple storage buckets in the distributed object storage cluster based on the operating parameters in the analysis cluster; generating corresponding dynamic recycling strategies for each storage bucket according to its dynamic load profile; and recycling garbage data from each storage bucket according to the dynamic recycling strategies. This application constructs dynamic load profiles of storage buckets based on the collected operating parameters, achieving real-time perception and accurate characterization of the cluster's load status. This allows for the generation of targeted dynamic recycling strategies adapted to the load characteristics of each storage bucket, replacing the traditional static threshold triggering mechanism. This avoids resource contention during peak business periods and solves the technical problem that the static threshold triggering mechanism for garbage data recycling cannot adapt to dynamic load changes, leading to system performance degradation.

The embodiment of the present application discloses a kind of ground source heat pump unit operating state detection method and system, first operating state data is generated by first heat pump operation activity data, when second heat pump operation activity data does not exist in specified task cycle, second operating state data is derived according to first operating state data, so even in the case without new data, the current state of heat pump can be reasonably estimated and predicted.This prediction mechanism provides necessary data support for second task issuing node, allows to determine the corresponding task issuing matching data according to the best available information in the case of incomplete data.In addition, it also includes the step of optimizing second operating state data according to the new operation activity data detected after the second task issuing node, to ensure that its operation strategy can be dynamically adjusted according to the latest real-time data, to improve the response speed and operation accuracy of ground source heat pump unit.

The present application relates to the technical field of edge computing, and discloses a cloud-edge collaborative Internet of Things platform mass data dynamic unloading processing method, comprising the following steps: step S1, collecting data; step S2, calculating total discharge rate; step S3, calculating the bending coefficient; step S4, calculating the cloud unloading ratio; step S5, calculating the expected completion time; step S6, calculating the priority quantity; and step S7, outputting the unloading matrix. The present application identifies data nonlinear backlog risk through the bending coefficient, generates a continuous adaptive unloading ratio, avoids decision distortion of a fixed threshold strategy, realizes direct conversion of executable instructions through unloading quantity aligned by protocol granularity, processes high-risk data flow preferentially through a bending-priority scheduling sequence, and suppresses data backlog formation, thereby adapting to the processing needs of sudden non-uniform mass data of an industrial Internet of Things and improving the stability of cloud-edge collaborative unloading.

The application provides a travel task data dynamic storage adjustment method and device and a medium, relates to the technical field of travel task data dynamic storage adjustment, and comprises the following steps: obtaining a plurality of task characteristics of each travel task corresponding to each aircraft task in a hot database; determining an initial travel task difference degree corresponding to each aircraft task; obtaining a target travel task difference degree corresponding to each aircraft task; determining an aircraft task with a target travel task difference degree greater than or equal to a preset travel task difference degree threshold as a target aircraft task; sending each travel task corresponding to the target aircraft task to a preset travel task establishment server; and sending each travel task corresponding to the first preset proportion of aircraft tasks in the YA to a cold database. The application can avoid low-value data from occupying valuable hot storage resources, and realizes the optimized utilization of hot database storage resources.

The application discloses a kind of multi-source data acquisition and knowledge enhanced intelligent analysis system, including sequentially connected adaptive multi-source acquisition module, dynamic knowledge fusion module, reasoning monitoring module and acquisition closed-loop feedback control module.Adaptive multi-source acquisition module is used to obtain time series sensing data and unstructured text data;Dynamic knowledge fusion module constructs dynamic knowledge graph, and the semantic conflict value of heterogeneous data is mapped to associated edge weight;Reasoning monitoring module is based on graph reasoning, and the comprehensive information entropy value of reasoning node is calculated in combination with output probability distribution and associated edge weight;When the entropy value is over standard, acquisition closed-loop feedback control module generates hardware control instruction according to the semantic attribute of key node, drives acquisition module to update acquisition strategy parameter and executes reacquisition.The application establishes the closed loop of semantic analysis to physical acquisition, realizes on-demand active acquisition based on analysis confidence, and significantly improves the intelligence and accuracy of analysis system.

The invention discloses a business processing time prediction method and device, a storage medium and electronic equipment, and relates to the technical field of information, the method comprises the steps of firstly obtaining dynamic feature data and static feature data, the dynamic feature data comprising processing equipment information and processing object information of a to-be-processed task; constructing a time prediction model according to the integrated learning model and the time sequence analysis model, and inputting the dynamic and static feature data into the time prediction model to obtain prediction processing time; and determining the target prediction time of the to-be-processed task according to the M prediction processing times. According to the method, dynamic and static feature data are comprehensively covered through dynamic and static multi-source data fusion, and the time prediction model can analyze the dynamic feature data based on the time sequence and can perform model optimization in real time according to the integrated learning model, so that the service processing time is predicted more accurately, and the service processing efficiency is improved. The prediction precision of the service processing time is improved, and the real-time response capability is enhanced.

The present application relates to the field of power grid dispatching data security, and more particularly to a power grid dispatching data dynamic perception and protection method based on a commercial secret algorithm. The method captures power grid dispatching network data streams in real time, obtains original service data containing dispatching instructions, measurement data and state information through protocol analysis and deep packet detection; then uses a dynamic data perception engine to identify sensitive data units, and dynamically generates data sensitivity labels according to the business type and the power grid operation state; dynamically matches commercial cryptographic algorithms from the commercial secret algorithm library according to the labels and distributes temporary session keys to generate an encryption strategy; encrypts the sensitive units, adds a security mark containing an algorithm identifier and a key index to the data packet header to form a protected data stream; sends the protected data stream to the target end, updates the session key state and uploads the execution log to the audit center. The present application realizes dynamic, accurate identification and differentiated encryption protection of power grid dispatching sensitive data.

This invention discloses a multi-module adaptive wall-climbing cleaning system and its control method. The system includes: a sensing module integrated on a main frame, which acquires wall environment data in real time and inputs it into a control module; a control module, including an embedded processor platform and multiple communication interfaces, which identifies contaminated areas by processing the received wall environment data, generates path instructions using a gray wolf optimization algorithm, and generates cleaning and adsorption instructions based on the contaminated area identification results; a motion module, which moves and adjusts the system's posture based on the path instructions; a cleaning module, including a replaceable cleaning tool unit, which matches the corresponding cleaning tool to the cleaning tool unit based on the cleaning instructions and performs cleaning; and an adsorption module, which dynamically adjusts the adsorption force based on adsorption instructions and real-time acquired adsorption state data to attach the system to the wall surface to be cleaned. This invention enables efficient, safe, and precise cleaning of complex walls, improving the level of automation.

This invention provides a method for rapid perception of the topology status of a satellite constellation network. It deploys a multi-dimensional physical layer monitoring module, a dynamic adaptive BFD detection mechanism, the OSPF routing protocol, and a shared data exchange area between the BFD driver and the OSPF process on each satellite node. This invention utilizes physical layer signal status monitoring technology and the rapid link status detection capability of the BFD protocol to monitor the connectivity of inter-satellite links in real time. Upon detecting a fault, it immediately notifies relevant nodes via control messages. Simultaneously, it links the BFD detection results with the OSPF routing protocol, triggering immediate route recalculation, thereby shortening route convergence time. This invention constructs a cross-layer closed-loop linkage system, dynamically adjusting protocol layer detection parameters through physical layer perception data, and combining hardware acceleration to optimize the entire fault detection process. This not only accelerates fault detection and recovery but also improves the resource utilization efficiency and overall transmission efficiency of the inter-satellite network, ensuring high network reliability and stability.

The application discloses a high-confidence data situation expression method based on timestamp cooperation, and relates to the technical field of data situation expression.The method comprises the following steps: multi-source timestamp cooperation calibration, timestamp-driven heterogeneous data dynamic fusion, time synchronization precision correlation confidence evaluation and situation generation, and high-confidence data situation visual expression.Through the construction of a hierarchical cascading timestamp cooperation calibration network, the absolute and relative time models are fused, the time alignment of multi-source heterogeneous data is realized at the microsecond level, the space-time dislocation problem caused by clock drift and network delay is fundamentally solved, the fusion efficiency and accuracy are significantly improved by taking the accurate timestamp as the driving force, dynamically dividing the fusion granularity and checking the time sequence consistency, the time synchronization precision is quantified as the confidence weight, and the dynamic confidence interval is generated by integrating the situation analysis, so that the evaluation result is changed from the subjective experience judgment to the objective and measurable reliable basis.

This invention discloses a dynamic evaluation method and system for game simulation performance based on entropy value method, belonging to the field of intelligent collaborative control technology. The method includes: constructing a prior knowledge base containing typical task sets, an evaluation index system, and performance functions; in simulation, identifying formation tasks in real time by parsing dynamic instructions and node states, and matching corresponding index systems for targeted data collection; dynamically calculating the aggregation weights of each level of indexes based on the real-time collected data using the entropy value method; and finally, using dynamic weights to weighted aggregate the index performance values ​​and outputting real-time performance evaluation results. This invention overcomes the problem of poor adaptability of traditional static evaluation methods in dynamic game scenarios, achieving dual dynamic adaptation of the index system and weights, significantly improving the real-time performance, objectivity, and accuracy of performance evaluation in large-scale autonomous simulation.

The application discloses an Android simulator game intelligent recommendation method and device and a readable storage medium, and comprises the following steps: firstly, multi-dimensional feature data of users and games on both sides is comprehensively collected to form a structured data set; through feature processing on the data, a standardized feature vector of the users and the games is constructed; based on the vectors, a multi-path recall, rough sorting, fine sorting and rearrangement cascading filtering process is adopted to generate a sorted recommendation list; the method can render and display the recommendation result according to the real-time simulator operation scene of the user, and collect user interaction feedback; finally, feedback data is used to dynamically update a model and strategy parameters to form a closed-loop iterative optimization system, so that more accurate and scene-based game recommendation is realized.

This invention relates to the fields of computer data processing and database technology, specifically to an intelligent search system for business objects based on metadata. The system includes: a context request parsing module: receiving abstract search requests and extracting environment parameters and permission features to generate a dynamic context snapshot; a logical structure construction module: combining snapshot execution rule injection operations to generate a logical abstract syntax tree containing implicit filtering conditions; a multi-dialect compilation and execution module: translating the syntax tree into physical execution statements matching the target storage engine dialect according to physical mapping rules; and an adaptive optimization feedback module: monitoring execution latency data and dynamically correcting the index strategy definition. This invention solves the maintenance bottleneck caused by the tight coupling between business logic and physical storage in heterogeneous data source environments, achieving zero-code modification and hot deployment of business logic.

The present application relates to carbon emission source inversion calculation technical field, especially to a kind of construction site carbon emission source inversion calculation method based on atmospheric diffusion model.The technical scheme includes the following steps: constructing space diffusion model: the meteorological parameter of construction site is obtained by meteorological monitoring equipment, pollutant concentration distribution is calculated based on atmospheric diffusion model, the model is corrected vertical diffusion by introducing mirror source term;Data dynamic noise reduction: the original monitoring data are filtered, and the balance between noise suppression and real fluctuation reservation is balanced by dynamic adjustment algorithm;Iterative inversion calculation;Comprehensive verification: by theory simulation and actual detection combination.The present application realizes the accurate, efficient and low-cost inversion of construction site carbon emission source by dynamically coupling meteorological-emission model, adaptive noise reduction algorithm and multi-source verification mechanism, which provides reliable technical support for real-time carbon management, carbon trading and green construction.

The application belongs to the technical field of medical information, and discloses a tumor chemotherapy scheme individualized adjustment and curative effect evaluation method and system. Static basic data, dynamic treatment data, single cell sequencing data and structured data of doctor-patient conversation are comprehensively collected in the data fusion quality control stage. Format adaptation and semantic alignment of cross-modal data are realized through a unified standardized interface. Data quality control is carried out in combination with an isolated forest algorithm, and only high-quality data with a score of 80 or more are included to provide a reliable basis for scheme development. In the multi-module collaborative prediction stage, a medical knowledge graph and a hybrid modeling framework are fused, multi-center data is jointly trained, and drug sensitivity scores are accurately output. When the scheme is generated, the clinical guidelines and patient needs are linked, multi-constraint rule reasoning and multi-objective optimization are used to develop individualized schemes that adapt to the patient's genetic characteristics, pathological types and quality of life demands, and reduce the risk of poor efficacy and serious adverse reactions caused by individual differences.