397 results about "Processing priority" patented technology

A system and method for adaptive real-time multi-modal compression with dynamic resource allocation provides intelligent compression optimization based on continuously monitored device conditions. The system monitors battery level, CPU utilization, and memory availability while classifying incoming multi-modal data streams comprising image, audio, text, and sensor data to determine processing priorities. Multi-objective optimization balances compression efficiency, reconstruction quality, and energy consumption using evolutionary algorithms that generate optimal parameters for an adaptive variational autoencoder. The autoencoder features dynamically selectable processing complexity, adjustable latent space dimensionality, and modality-specific processing layers. The system automatically switches between operational modes including emergency mode triggered by resource constraints, which applies maximum compression settings and intelligent data triage. Continuous learning adapts compression parameters based on observed performance outcomes, improving future optimization decisions. The system enables homomorphic operations on compressed data and provides enhanced compression performance under varying resource constraints across diverse edge computing applications.

The invention relates to the technical field of project management, in particular to a building engineering project construction quality management method and system, and the method comprises the following steps: obtaining a drawing node sequence index and comparing a process stage number, screening compliant nodes, judging the reasonability of a task configuration time sequence, analyzing the deviation of an included angle between a crack angle and a load direction, and recognizing structural abnormality. And aggregating the partition abnormal nodes to form a construction project quality risk distribution section mapping result. According to the method, the structure drawing node sequence is compared with the construction process, it is guaranteed that input data logic is unified, the task configuration reasonability is improved through input time and stage sequence cross check, a stress deviation judgment mechanism is established in the crack direction through vector included angle and load comparison, and structural logic verification of inspection data is achieved; abnormal nodes are identified according to double standards of time compliance and stress deviation, a spatial density model is constructed by combining partition aggregation with an area ratio, building quality risk distribution is accurately presented, and the problem focusing and processing priority judgment capability is enhanced.

The invention discloses a database data real-time synchronization method and device, and relates to the technical field of data synchronization, the method comprises the following specific steps: S100, task receiving and preprocessing: receiving a synchronization task request from a source database, including a to-be-synchronized data set and target database information, and performing data format verification and duplicate removal processing; s200, performing priority evaluation and sorting: performing priority evaluation on the synchronization tasks according to a preset rule, and performing sorting according to priorities; according to the method, the priority and the data volume of the synchronization task and the load condition of the target database are dynamically evaluated through an intelligent scheduling and load balancing mechanism, so that the execution sequence and the speed of the synchronization task are intelligently adjusted, and the task with high priority can be preferentially processed; and meanwhile, resource waste on low-load nodes or overload on high-load nodes are avoided.

The invention provides a construction dynamic twinning method based on the Internet of Things and BIM, and relates to the technical field of digital twinning, and the method comprises the steps: obtaining heterogeneous data streams collected by a sensor, and carrying out the analysis and classification of the data streams, and generating a standardized data set; performing semantic mapping on the standardized data set according to association rules of BIM component identifiers and data attributes to generate a component association data set; decrypting and decompressing the encrypted data packet at the cloud, analyzing the construction progress time sequence data by adopting a distributed computing framework, and generating a deviation detection result; dynamically adjusting a routing rule of a data link according to a deviation detection result, and redistributing a processing priority to optimize link configuration; updating a BIM component state based on the optimized link configuration, and generating a real-time updated digital twin model by adopting cloud computing resources; three-dimensional visual data are extracted from the digital twin model and mapped to a BIM model interface by adopting a rendering technology, so that the monitoring precision and the management efficiency of the construction process are effectively improved.

The invention discloses a two-stage scheduling model and scheduling method based on a heterogeneous multi-core processor, and relates to the technical field of computer science, the model comprises an associated subtask acquisition module used for analyzing a target task and generating a plurality of associated subtasks; the container distribution analysis module executes first-level scheduling and distributes sub-tasks to K task containers; the static priority configuration module performs second-level scheduling on the sub-tasks according to the dependency relationship to generate a processing priority sequence; the container scheduling structure generation module creates a container scheduling structure; the window distribution execution module forms a cyclic scheduling sub-sequence; and the task cross-container dependency processing module performs cross-container dependency management in the task execution process to ensure the scheduling coherence and the execution of the dependency relationship. The technical problems that in an existing heterogeneous multi-core processor, the complex task scheduling efficiency is low, and task execution is unstable are solved, and the technical effect of improving the task scheduling efficiency and the task execution stability is achieved.

The invention relates to the technical field of distributed agent collaboration and graph database query optimization, in particular to a graph query processing method and system based on multi-agent collaboration, and the method comprises the following steps: reasoning a coordination agent to analyze the semantics and intention of user query by using a large language model; a structured multi-agent execution plan is output, and an entity search agent or a relation analysis agent needing to be called is explicitly called; the agent coordinator receives the multi-agent execution plan and selects agents according to task types and task allocation; obtaining a distributed intermediate result set; starting a result aggregation mechanism, and performing typed processing, priority ranking and deduplication merging on the distributed intermediate result set to obtain an arrangement result; and outputting an answer for answering the initial question of the user. The system comprises an agent execution plan output module, a multi-task execution module and an arrangement result reasoning module. According to the method, efficient, extensible and fault-tolerant graph query processing is realized.

The invention relates to the technical field of order processing, and discloses a member order processing method, device and equipment and a storage medium, and the method comprises the steps: collecting multi-platform member information, constructing a member graph structure, and carrying out the node feature extraction, and obtaining a multi-dimensional member feature vector; performing feature fusion on the multi-dimensional member feature vector and the to-be-processed order data to obtain a member-order fusion feature vector; order classification is carried out to obtain an order classification result and a processing priority; performing multi-platform collaborative integer programming and solving to obtain a cross-platform order allocation scheme; performing member value evaluation to obtain a dynamic member value score and hierarchical division information; and inputting the dynamic member value score and the hierarchical division information into a dynamic right and interest distribution model based on the deep Q network for right and interest distribution strategy optimization to obtain a personalized member right and interest combination, and the method can comprehensively utilize multi-platform data to realize intelligent order processing and dynamic right and interest distribution.

According to the priority asynchronous processing method and system for network security, multiple data sources are integrated, the threat level of each data packet is evaluated in real time, and the processing priority of each data packet is dynamically adjusted according to the threat level. Different from a traditional static method, the method provided by the invention utilizes an advanced machine learning algorithm, can perform dynamic evaluation in multiple dimensions, and timely identifies and preferentially processes high-risk data packets. The mechanism obviously improves the response capability of the system to novel and complex attacks. Meanwhile, a multi-node cooperative attack response mechanism is introduced, when a certain node detects abnormal traffic, other nodes can be automatically notified, threat situation information can be shared, and therefore rapid cooperative reaction is achieved. The integrated innovation not only enhances the overall security of the network, but also optimizes the data packet processing efficiency, effectively solves the main defects in the traditional network security system, and provides a new thought for constructing a safer and more flexible network environment.

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 relates to the technical field of data exchange, in particular to a markup language-based data exchange method and system, and the method comprises the following steps: determining a processing priority, monitoring a load and adjusting a processing sequence, optimizing IO response time, recognizing a redundant field and evaluating a key risk, and executing key updating based on the number and complexity of data packet labels. And the tag analysis accuracy and efficiency are optimized. According to the invention, through accurate analysis of the markup language in the data packet, scheduling, transmission and analysis in the data exchange process can be optimized, and evaluation of the number of labels, the complexity of the nested structure and the field length can be realized, so that each data packet can dynamically allocate priority according to the characteristics of the data packet, thereby effectively improving the data transmission efficiency, reducing the delay and improving the data exchange efficiency. By monitoring the load and the transmission opportunity of the data packets in real time, the processing sequence of the data packets can be dynamically adjusted, and resource waste caused by overload of the data exchange system is reduced.

The invention discloses a data updating method and device for a water conservancy knowledge graph and a medium, and relates to the field of water conservancy data management, and the method comprises the steps: constructing an initial water conservancy knowledge graph based on a plurality of data sources of water conservancy data; monitoring the plurality of data sources, and judging whether a data change event is triggered or not; when the data change event is triggered, generating a knowledge graph updating task through a preset synchronization rule; when the number of the knowledge graph updating tasks is greater than 1, determining the processing priority of the knowledge graph updating tasks according to the importance of updating graph nodes in the water conservancy knowledge graph, and generating an updating task queue; and executing the update task queue, updating the water conservancy knowledge graph, and recording an update version snapshot. Through unified monitoring of a structured data source, an unstructured data source and an interface data source, the island effect of water conservancy data is broken, and unified linkage updating of cross-modal data such as reservoir attributes, monitoring reports and real-time water levels is achieved.

The invention relates to the technical field of power equipment supply chain management, and discloses a power equipment supply chain collaborative management system based on an alliance chain, comprising an alliance chain network layer: a distributed network composed of a manufacturer node, a supplier node, a logistics node, a detection node and a grid company node, each node maintaining account book consistency through a consensus algorithm; the intelligent contract execution layer comprises an order processing contract, a logistics tracking contract, a quality acceptance contract and a settlement management contract, and supports automatic execution of a business process; and the data management platform is provided with a distributed storage unit, an encryption transmission unit and an authority control unit and is used for realizing encryption storage and hierarchical access of key data. Full-process automation of order matching, production plan generation and logistics tracking is realized through an intelligent contract execution layer, an AI prediction module can pre-judge a demand peak value in advance based on historical data, a node processing priority is optimized in combination with a dynamic consensus algorithm, and manufacturer order response time is compressed.

The invention discloses a multi-machine resource configuration management method and device, equipment, a medium and a product, and relates to the technical field of multi-machine resource configuration.The method comprises the steps that queue allocation is conducted on satellites according to processing priorities; distributing machine nodes for each job queue according to machine node resources required by the job queues to obtain a plurality of job queues and a plurality of corresponding machine node groups; acquiring state information of each host node in the machine node group, host resource load information and resource information required by each job in the job queue in real time, and matching each job in the job queue to the machine node in the corresponding machine node group according to the state information and the host resource load information of each host node in the machine node group; and activating the jobs meeting the conditions one by one according to the priority of each job in the job queue and executing the jobs in parallel. The whole computer network system is changed into a relatively single virtual host or super computer, so that the effect of providing a relatively single service operation platform for upper-layer conventional service scheduling is realized.

The invention provides a multi-modal content generation AI model construction method and device based on a diffusion model, and relates to the technical field of content generation. The method comprises a multi-source data processing module, a modal priority analysis module, a serialized modal processing module, a diffusion parameter adaptive adjustment module, an interactive feedback integration module and a collaborative output adjustment module. According to the method, multi-modal data input is integrated, model parameters are dynamically adjusted, information entropy is used for evaluating the information amount of the data, the processing priority is set according to the information amount, the recognition capacity of the model for data importance is enhanced, the model parameters are adjusted in real time to adapt to the characteristics of different data modalities, and the accuracy of data processing is improved. And the generation parameters are dynamically adjusted through user feedback, so that the generated content better fits the actual demand and preference of the user, and the consistency and integration of the content are ensured, the attraction of the content is improved and the propagation effect of the content is enhanced by coordinating the style, theme and emotion of the output content.

The invention provides an integral shopping mall order rolling processing optimization method and system based on big data, and the method comprises the steps: employing a dynamic priority adjustment mechanism for a conflict order list, and adjusting the order processing priority based on the user behavior track data, including historical exchange preference, and obtaining a resource distribution scheme; integrating the order sequence through a queue reordering mechanism, reordering based on the resource allocation scheme to obtain a final processing sequence, preferentially executing the high-priority request, and maintaining the queue stability at the same time; if residual conflicts exist in the final processing sequence, supplementary resources are extracted from a preset standby inventory through a standby resource set scheduling mechanism, a complete execution plan is obtained, and the plan covers all order processing paths; and on the basis of the complete execution plan, monitoring the order processing progress, and obtaining a stable operation order flow through progress tracking and anomaly detection, real-time state feedback and iterative adjustment.

The invention relates to the technical field of automatic operation and maintenance of a power system, in particular to an automatic operation and maintenance method and system for plant-station equipment based on a knowledge graph, and the method comprises the steps: collecting static ledger data, real-time operation data and historical operation and maintenance data of the plant-station equipment, constructing a multi-dimensional association knowledge graph, creating a digital twinborn body for target equipment in a plant station, and carrying out the operation and maintenance of the plant-station equipment. Establishing a bidirectional data channel between the digital twin and a corresponding equipment entity node in the knowledge graph; and based on a state evaluation rule and a fault propagation path model preset in the knowledge graph, performing real-time health state evaluation on the target equipment by using the state evaluation rule and the fault propagation path model to generate a health index, and when an abnormality is monitored, tracing along the topological relation between the electrical connection and the equipment in the knowledge graph, the fault source is positioned, the confidence probability is calculated, risk level evaluation and processing priority ranking are carried out according to the confidence probability, an operation and maintenance diagnosis work order containing an execution time sequence is obtained, and the fault reason can be quickly traced and positioned.

The invention discloses a table-level data classification and grading method and system based on big data, and relates to the technical field of table-level data classification and grading. According to the scheme, second-level sensitive table grading response is achieved through streaming incremental calculation and dynamic semantic coupling; a finite-state machine and a Hash fingerprint technology accurately capture table structure and content mutation, and traditional batch processing delay is avoided; the multi-modal fusion model synchronously analyzes topological features and semantic vectors, and the field-level sensitivity misjudgment problem is solved; the timeliness weight mechanism guarantees real-time evaluation of a dynamic association table relationship, and is particularly suitable for a high-frequency change scene in a big promotion period; and the asynchronous architecture design isolates the calculation load, so that the processing priority of the core price list is effectively guaranteed.

Instead of a system that does not address host buffer fragmentation or saturation, utilize a different metric for command prioritization. Commands are re-ordered and prioritized based on the number of outstanding host buffers that will be released on command completion, thereby limiting and / or reducing the physical address fragmentation and host memory overhead. Command processing priority will take the number of host memory page segments represented by the command into consideration.

An artificial intelligence priority notification method and a related apparatus. The method comprises: a terminal generating first information, the first information being used to indicate a processing priority of a data unit, wherein the processing priority is used to allocate processing resources to the data unit, and the data unit is used for AI inference and / or training tasks; and, the terminal sending the first information. Hence, in this method, the terminal or a server can mark a processing priority of a data unit for an AI task, so that a network side can allocate processing resources on the basis of the processing priority, thereby improving the utilization of processing resources of the network and alleviating the problem of computing power shortage.

The invention discloses a campus equipment operation and maintenance management and control platform based on intelligent control. The platform comprises a detection module, an abnormity analysis module and a fault positioning processing module. The detection module constructs a risk vector and a cobweb coordinate system, and starts a balanced or centralized detection mode according to the cobweb area and the axial value dispersion; the anomaly analysis module judges abnormal components and marks priorities by constructing a component data matrix, analyzing a time sequence and the like; the fault positioning processing module calculates abnormal component correlation, generates a fault feature cluster, matches fault types and sorts and processes a priority sequence; according to the platform, the problems of missing multi-dimensional risk analysis, extensive fault positioning and the like in traditional operation and maintenance are solved, accurate assessment and grading detection of equipment risks, accurate judgment of abnormal components and topological positioning and scientific scheduling of faults are realized, the accuracy and efficiency of campus equipment operation and maintenance are improved, and safe and efficient operation of equipment is guaranteed.

The invention provides a database access method based on an end-side cloud system and related equipment. The method comprises the following steps: constructing the end-side cloud system of a terminal, an edge gateway and a cloud server; deploying an enterprise metadata knowledge base, an AI model and an enterprise database in the end-side cloud system based on customer requirements; receiving a demand prompt word input by a user through an intelligent agent in the terminal; a routing strategy is obtained through an intelligent agent based on deployment situations of an enterprise metadata knowledge base, an AI model and an enterprise database and by taking local gateway processing priority as a criterion; and based on the routing processing strategy, the edge gateway and the cloud server carry out programmed processing on the demand cue word. According to the database access method, the AI model is used for code generation, the development difficulty is reduced, the enterprise metadata knowledge base, the AI model and the enterprise database are flexibly deployed based on customer requirements, the terminal intelligent agent can flexibly route, and the database access method has better adaptability and can better meet the enterprise requirements.

The invention relates to the technical field of data processing. The invention discloses a monitoring system and method for a distribution network construction process and a computer readable storage medium. The monitoring system for the distribution network construction process comprises a power failure information collector, a power failure event analysis unit, a power failure event sending unit and a power failure event monitoring unit. The power failure information collector is used for acquiring power failure event data. And the power failure event analysis unit is used for obtaining the corrected power failure event data. And the power failure event sending unit is used for sending the business processing items with the updated processing priorities to a corresponding application system. And the power failure event monitoring unit is used for monitoring service processing items and obtaining fault node information and the latest state of service processing, and the power failure event monitoring unit displays the fault node information and the information of the service processing items in real time through a visual interface. According to the monitoring system, unified management of power failure event information can be realized, and the safety operation risk of a power grid is reduced.

The invention provides an autonomous controllable anti-interference time synchronization method and device based on Beidou, and belongs to the technical field of satellites, and the method specifically comprises the steps: obtaining the distribution data of different time synchronization modes which are determined to be time synchronization deviation time periods in different time periods, and employing the distribution data of the time synchronization deviation time periods which are determined to be time synchronization deviation time periods, determining a time synchronization processing time period and a time synchronization processing priority in the time period, determining a priority time synchronization processing time period by using the time synchronization processing priority, and obtaining time synchronization processing results of different time synchronization modes in the priority time synchronization processing time period; determining an adjustment processing strategy of the priority time synchronization processing period according to correction processing data in the priority time synchronization processing period and the time synchronization processing priority when it is determined that correction processing of the target device needs to be carried out in combination with distribution data of different time synchronization modes in the time synchronization deviation period in the priority time synchronization processing period, and determining the adjustment processing strategy of the priority time synchronization processing period according to the correction processing data in the priority time synchronization processing period and the time synchronization processing priority; therefore, the accuracy of time synchronization processing is improved.

The invention discloses a master control multi-serial port concurrent cooperative communication method, electronic equipment and a storage medium. The communication method comprises the following steps: acquiring a serial port communication speed and a data processing speed; constructing a cache circular queue according to the serial port communication speed and the data processing speed; acquiring at least one piece of data information transmitted from the serial port group; wherein the data information comprises a corresponding serial port identifier; generating an interrupt instruction according to the data information, and sequentially storing the data information at corresponding positions in a cache circular queue according to a serial port identifier of each piece of data information, a preset priority sequence and a write pointer of the cache circular queue; wherein the priority sequence is used for representing the processing priority of each serial port in the serial port group; and extracting the data information from a corresponding position in the cache circular queue according to a read pointer of the cache circular queue, and performing data processing on the data information. According to the invention, data loss of the serial port during communication can be avoided, and the data transmission reliability is improved.

The invention provides a real-time data processing method and system based on edge computing, and relates to the technical field of data processing.The data validity period is calculated through a composite decision model of terminal equipment physical sampling frequency constraint and preset service rules, the signal restoration accuracy requirement and the service scene emergency degree are effectively balanced, and the real-time data processing efficiency is improved. Overtime failure of key data or occupation of non-key data resources is avoided; the data transmission integrity in a bandwidth fluctuation environment is improved through a dynamic window cutting mechanism driven by a real-time network state; optimizing edge computing power load distribution in combination with a routing decision mapping strategy and a processing priority resource ratio; the terminal instruction reliability is improved based on hierarchical control of historical data abnormal value purification and geometric distance measurement; a complete technical chain from data acquisition, self-adaptive transmission cutting, aging precise arbitration and routing resource collaboration to closed-loop control feedback is formed, and the transmission efficiency, the resource utilization precision and the control stability of high-concurrency real-time data processing are enhanced.

The invention discloses a queue message processing method and device, a hard disk, a medium and a product, and relates to the technical field of message scheduling, and the method comprises the steps: respectively configuring a corresponding queue message number threshold and a message processing number threshold for each message queue; different message queues correspond to different queue priorities; determining a processing priority of each message queue based on a size relationship between the number of messages in the message queue and a corresponding queue message number threshold in combination with the queue priority; and performing message processing on each message queue in sequence according to the processing priority, and controlling the message quantity of the processed messages to be not greater than a corresponding message processing quantity threshold when the message processing is performed on any message queue every time. In this way, the processing priority can be re-determined according to the actual condition of the message queue by combining the queue priority and the queue message number threshold value; long-time resource occupation can be avoided, and the overall response speed and the message processing efficiency of the system are improved.

The invention provides a multi-modal data archiving processing system based on cloud computing, and relates to the technical field of data processing, and the system is used for obtaining an archiving request and an archiving task, determining an archiving type, a processing priority and a task number according to the archiving request and the archiving task, recording a memory identifier, an execution path and a cache address of a processing node, and storing the memory identifier, the execution path and the cache address of the processing node; the method comprises the following steps: extracting a structured field group and an unstructured content block of an archiving task, mapping the structured field group according to fields to generate a structure reference table, segmenting the unstructured content block according to a time sequence to generate a content time stream, recording each field mapping and time segmentation operation, and determining a reference relationship between each field mapping and time segmentation operation and a processing node; and determining a task number, a resource state and a data fragment of each processing node to obtain state anchoring data, combining the structure reference table and the content time stream with the state anchoring data into a double-layer archiving component, and archiving the double-layer archiving component. According to the method, content backtracking and operation backtracking can be carried out on the multi-modal data archiving process.

The invention provides a grid governance event management method and system based on an event circulation mechanism, and a medium, and relates to the technical field of data processing, and the method comprises the steps: arranging edge grid nodes for a plurality of grid regions in a target governance region; after receiving and analyzing the first task scheduling strategy uploaded by the first edge grid node, the grid governance holder judges resource scheduling conflicts of concurrent events and calls out M conflict scheduling strategies of M grid governance events; and carrying out resource allocation optimization on the first task scheduling strategy and the M conflict scheduling strategies based on the event processing priority, outputting M + 1 optimized scheduling strategies, and carrying out processing task cross-department distribution. The technical problems that in the prior art, due to the fact that resource allocation cannot be dynamically adjusted, resource scheduling conflicts are likely to be generated under the condition of multi-task concurrence, the event treatment efficiency is low, and the response speed is low are solved, and the technical effects of improving the event treatment efficiency and enhancing the collaborative treatment capacity are achieved.

The invention relates to a task processing method and device, computer equipment, a storage medium and a computer program product. The method comprises the steps of obtaining task information corresponding to a to-be-processed task, and obtaining current load information of a candidate task processing unit associated with the to-be-processed task; the candidate task processing unit at least comprises two thread units and two process units; determining a processing priority corresponding to the to-be-processed task according to the task information; determining a target task processing unit corresponding to the to-be-processed task from the candidate task processing units according to the processing priority and the current load information; distributing the to-be-processed task to a corresponding target task processing unit, and enabling the target task processing unit to process the to-be-processed task; the processing state of the to-be-processed task is used for updating the number of the candidate task processing units. By adopting the method, the task processing efficiency can be improved.

The invention belongs to the technical field of data association analysis processing, and discloses an industrial control system multi-modal data association analysis method based on a knowledge graph. Comprising the following steps: reading multi-modal data of equipment in an industrial control network; obtaining an initial industrial multi-modal sub-knowledge graph of each device at different time points through the multi-modal data and the mutual influence relationship between the multi-modal data, and further obtaining an initial industrial multi-modal knowledge graph; corresponding nodes in the initial industrial multi-mode knowledge graph are connected according to the physical connection relation between the devices, and a final industrial multi-mode knowledge graph is obtained; according to the connection relation between the nodes in the final industrial multi-mode knowledge graph, obtaining an exception handling priority judgment coefficient of the equipment, obtaining an exception handling priority of the equipment through the exception handling priority judgment coefficient of the equipment, and carrying out exception handling on the equipment according to the exception handling priority of the equipment; and the real-time performance of data association analysis is further improved.