193 results about "Data contention" patented technology

The invention discloses a multi-modal fusion AGV dynamic path planning and cluster scheduling system, and relates to the technical field of multi-modal perception and data fusion, and the system comprises a multi-modal perception module which generates a dynamic obstacle confidence map through multi-source data fusion in combination with a hardware-level time synchronization and Transform feature fusion network; the dynamic path planning module adopts an improved rolling window algorithm, integrates an LSTM space-time conflict prediction model and an adaptive weight cost function, and realizes dynamic obstacle trajectory prediction and non-oscillation global path generation; the cluster scheduling control module is used for optimizing multi-AGV task allocation and conflict resolution in combination with a dynamic priority preemption mechanism and digital twinborn simulation rehearsal based on a distributed contract network protocol of edge computing; and the data conflict resolution module is used for triggering a multi-modal re-calibration process through confidence weighting and sliding window time sequence verification. According to the system, in logistics storage and intelligent manufacturing scenes, the dynamic obstacle avoidance success rate and the robustness and operation efficiency of an AGV cluster are improved.

The invention relates to the technical field of accounting informatization, and discloses an accounting document cross-platform synchronization system based on a block chain and a conflict processing method, and the system automatically judges a multi-mechanism concurrent operation conflict based on a preset medical authority level and a millisecond timestamp. And when a plurality of branch hospitals modify the same patient voucher at the same time, preferentially adopting a high-authority mechanism to operate, if the authority is at the same level, selecting the operation with the latest timestamp, and if logic conflicts exist, pushing to a general hospital for manual auditing. And an operation log is recorded in real time by adopting Apache Kafka, and a non-tampering historical version is generated through a block chain technology. All modification records are stored in a Merkle tree structure, a complete operation track at any time point can be inquired through a patient ID, the complete operation track comprises modification content, operator identity and block chain transaction hash, a national medical insurance platform is connected in real time, and cost compliance is automatically verified; the system can solve the problems of data conflicts, version chaos and auditing tracing among heterogeneous ERP (Enterprise Resource Planning) systems.

The invention relates to the technical field of information auditing management, in particular to a personnel archive information extraction intelligent auditing method and system based on a large language model, and the method comprises the following steps: generating a timeline sequence and an attribute feature set which are separated through spatial-temporal feature decoupling; performing cross-modal alignment verification on the timeline sequence and the attribute feature set, and outputting a time-space consistency map with conflict marks; generating a risk conduction probability matrix by analyzing abnormal nodes; calculating timeline credibility, attribute credibility and association credibility to form a three-dimensional credibility vector; and automatically executing logic self-consistent repair or generating an audit report comprising a contradictory traceability path. According to the method, the traceability path and the influence weight of the data conflict are provided, a visual basis is provided for manual auditing, and the conflict judgment efficiency in a complex data environment is improved.

The invention provides a knowledge base and business system collaboration method under an AI platform, and belongs to the technical field of AI platform digital data processing.The method includes the steps that triple semantic analysis is conducted on query by constructing a multi-level semantic vector representation module, a parallel data retrieval engine is started, vector retrieval, graph reasoning and real-time data pulling are executed at the same time, and the query efficiency is improved; establishing a dynamic confidence evaluation mechanism to evaluate the quality of the data source, executing a weight distribution algorithm based on reinforcement learning, dynamically calculating the weight of the data source according to a query type by adopting a graph convolutional network intelligent routing decision model, and implementing multi-source data fusion and consistency verification to solve data conflicts through a weighted voting mechanism. An intelligent result sorting and filtering system is established, a multi-dimensional evaluation strategy is adopted to output high-quality answers, a continuous learning and feedback optimization loop is constructed, system performance is continuously optimized through active learning and a graph shortest path algorithm, and the technical problem that knowledge base data and a service system cannot effectively and uniformly make decisions is solved.

The invention discloses a PLC scheduling algorithm based on a multi-core soft real-time operating system, and relates to the technical field of voltage control, and the algorithm comprises the following four steps: 1, starting a target industrial control system, completing hardware self-inspection, memory allocation and communication module starting, and sending an initialization ready signal after confirming that an assembly is normal; 2, according to PLC task functions and real-time performance, four types of standardized tasks are divided, priority levels are defined, sub-priorities are configured, a dependency relationship is identified, and a task chain is established; 3, counting the number of tasks and task chains, distributing resources by using multiple binding cores, and constructing a global ready queue to adapt to dynamic scheduling; and 4, monitoring an interrupt event through an interrupt manager, realizing high-priority task preemption by semaphores, and allocating tasks to corresponding CPU cores, so that the problems of soft real-time multi-core task preemption and data conflict are solved, the scheduling real-time performance and the data security are improved, the system failure rate is reduced, and the industrial control efficiency and stability are improved.

The invention relates to the technical field of medical information, and particularly discloses an ERP (Enterprise Resource Planning) integration-based medicine transaction data synchronization system, which comprises a data acquisition module, a mapping analysis module, a data fusion module, a trend analysis module and a center console module. According to the scheme, the multi-dimensional feature space is constructed, the field structures in different service systems are identified and mapped to the uniform target field set to construct the dynamic mapping table, and the adaptability to different service systems is enhanced; a dynamic updating mechanism based on event driving is designed, complex business logic is flexibly handled, the system load is reduced, the system operation efficiency is improved, the compliance of a business process is ensured through cooperation of a rule engine, and the problem of data conflict possibly occurring in the data synchronization process of multiple business departments is solved; and a center console is arranged to monitor efficient circulation of medicine transaction data, so that the stability and safety of data exchange are ensured, a reliable tracing basis is provided for medicine supervision, and subsequent analysis and maintenance are facilitated.

The invention provides a data synchronization method and device based on Spring Batch and a large model. Synchronously initializing a large model micro service and a Spring Batch framework, and establishing a model service hot standby mechanism; obtaining data source features through a metadata scanning engine driven by a large model, and generating an adaptive synchronization strategy; optimizing a query plan based on the synchronization strategy, dynamically controlling data fragmentation and executing streaming preprocessing and semantic mapping conversion; a target table structure is adapted, a three-level conflict detection mechanism is adopted to eliminate data conflicts, and meanwhile transaction processing and batch writing logic are optimized; the data quality is verified through three-level verification, performance parameters are dynamically adjusted and optimized, and fault-tolerant recovery and resource elastic expansion and contraction are achieved; metadata are synchronized, an execution report is generated, knowledge base self-learning is completed based on task full-link indexes, and a data consanguinity map and a reusable processing case library are constructed. According to the scheme, diversified and dynamic enterprise data synchronization requirements can be met.

The embodiment of the invention provides a data conflict automatic solution method and device, electronic equipment and a medium, and the method comprises the steps: automatically recognizing a data conflict through text comparison and semantic analysis; based on a rule base and a reinforcement learning algorithm, dynamically selecting an optimal conflict resolution rule based on the identified data conflict, and executing the conflict resolution rule; selecting an optimal version to be executed according to the conflict resolution rule, carrying out data merging, and storing key information of conflict data; under the condition that the integrity of AI language large model training data is guaranteed, redundant data is removed from the merged conflict data, and incremental updating is carried out.

The invention discloses a service entity intelligent prediction system and method oriented to multi-dimensional decision support, and relates to the technical field of service prediction. The system comprises a service multi-source data screening module, a service multi-source data correction module and a service entity dimension index output module. According to the method, data fusion is carried out on the multi-source data of each dimension index, an adaptive data screening strategy is selected according to the data conflict detection condition in the process, and then data range verification is carried out on each to-be-input data determined by the data screening strategy; and determining whether to perform data deviation determination based on the verification result so as to determine whether to execute data correction measures, finally, after data fusion, inputting the determined to-be-input data into the prediction model, and outputting each dimension index after index data range determination and a determination result prompt. The intelligent prediction precision of the service entity is improved, and the problem that the intelligent prediction precision of the service entity is reduced in the prior art is solved.

The invention discloses a foreground and background state information intelligent synchronization method in project management. The method comprises the following steps: S1, constructing a three-layer architecture of a foreground system, a state storage center and a background system; s2, initializing a state; s3, realizing state synchronization of the foreground system and the background system through at least one synchronization mode; s4, constructing a version control and conflict resolution mechanism, when the state of each project is updated, the foreground system and the background system carry version numbers, checking the consistency between the client version number of the foreground system and the server version number of the background system when the update is submitted, if the client version number of the foreground system and the server version number of the background system are consistent, executing state updating and progressively increasing the version number, and if the version number of each project is not consistent, executing state updating and progressively increasing the version number; if yes, judging that the data conflict exists, automatically executing a preset conflict solving strategy, and broadcasting a resolution result to a foreground system and a background system. The method has the advantages that the item switching state is not lost, background state change and foreground real-time response are achieved, and conflicts are automatically eliminated without manual intervention.

The present application relates to the technical field of parallel processing, and provides a parallel processing method and system for batch write-off tasks. The method comprises: extracting a plurality of pieces of query data of a preset write-off window, comprising external write-off codes and write-off services; performing file import on the basis of the data, and generating transaction files with unique identifiers; when file name identifiers are verified, parsing the external write-off codes, and generating fund files; generating pending write-off files by means of procurement-settlement mapping authentication; identifying request time identifiers to identify write-off conflicts, and generating conflicting file clusters; updating the configuration of a parallel processing module on the basis of the conflict condition; and utilizing the updated module to process the conflicting file clusters in parallel. The present application solves the technical problems of data conflict, irrational resource allocation and low processing efficiency caused by improper parallel processing in batch write-off tasks, and realizes real-time extraction, verification, parsing and authentication of write-off data, thereby ensuring the data accuracy and consistency.

The invention discloses a data conflict processing method and device, equipment and a medium, and relates to the technical field of object storage. According to the scheme, a conflict detection model used for conflict detection and a conflict processing model used for conflict processing are generated in advance by using historical object storage service operation records; when an object storage service operation record of the data center is collected, conflict detection can be realized through the conflict detection model; when it is confirmed that conflicts exist, the optimal conflict processing strategy can be automatically recommended through the conflict processing model, and therefore the requirement for manual intervention is reduced while the detection accuracy is improved; compared with a traditional rule, the automatic conflict detection and recommendation conflict processing scheme is especially suitable for a complex conflict situation, and the data conflict processing efficiency is improved.

The invention relates to an inventory data synchronization and consistency verification system supporting network disconnection fault tolerance, and discloses an inventory data synchronization and consistency verification system which realizes continuous recording of inventory operation during a network disconnection period through network state detection and local cache, performs batch transmission after network recovery through a synchronous uploading and verification mechanism, and ensures data integrity. According to the inventory data synchronization and consistency verification system supporting network disconnection fault tolerance, data conflicts are automatically solved through a conflict detection and strategy processing module, a difference report is generated through consistency verification, and secondary synchronization is executed, so that safe synchronization and final consistency guarantee of inventory data are achieved, and it is ensured that the service process is continuous and stable. The system is characterized by comprising a network state detection module, a local cache module, a transaction log management module, a synchronous uploading module, a conflict detection module, a conflict resolution strategy module, a consistency verification module and an abnormity alarm and manual intervention interface module.

The invention relates to the technical field of distributed data synchronization, in particular to a three-terminal message synchronization method, which comprises the following steps of: generating FALCON public and private keys for three terminals respectively, negotiating a two-threshold threshold public key, writing a message key hash with a vector clock into a multi-branch Verkle tree, and updating a root abstract; a sending end carries out integrity proof broadcasting through a Bloom bitmap, a compression model, a root abstract and zero knowledge; a receiving end compares the bitmaps to obtain a difference set, and a coding window, a redundancy proportion and power distribution are obtained through reinforcement learning; a sending end uses sparse Fountain coding to send difference set packets in wireless and optical links in a shunting manner; a receiving end carries out linear solution decoding, verification and certification, batch box opening, supplementary signing aggregation and root abstract refreshing; and the completion rate and the link quality are continuously written, and self-adaptive operation is carried out in offline, alternating or low-power scenes. The method has the advantages of quantum security, low bandwidth, low time delay and energy conservation, and transaction omission and data conflict can be avoided.

The invention relates to the technical field of data management, in particular to a cross-platform advertisement putting and SEO collaborative optimization system which comprises a resource time sequence scheduling module, a keyword screening module, a putting path construction module, a data conflict comparison module and a content archiving and auditing module. According to the invention, through association mining of multi-platform advertisement data and user behaviors, real-time mapping of time sequence distribution of put resources and user group states, and dynamic integration of budget weights and audience portraits in a keyword selection process, a multi-parameter interactive screening mechanism is formed for advertisement paths; text similarity judgment and conflict source tracing are synchronously introduced into channel content, an archiving standard is jointly defined by content change frequency and source credibility, data in each link automatically adjusts an attribution boundary according to a change trend, multi-source data validity is accurately distinguished in an archiving process, and structure-level linkage is realized by advertisement circulation, content integration, path adaptation and conflict detection. And the consistency and uniqueness of data updating and archiving are guaranteed.

The invention discloses a third-party cloud service data synchronization processing method and system based on a timed task, and the method carries out the attribute configuration of the timed task through a management interface, and the objects of the attribute configuration comprise execution time, frequency, a third-party cloud service data source and target system information. Storing the object of the attribute configuration in an attribute database; when the timed task is triggered, acquiring data from a third-party cloud service in an asynchronous mode, storing the data to a local cache, and recording a data identifier; synchronizing the processed data to a target system by adopting an incremental synchronization strategy according to the data identifier, and performing conflict detection and conflict resolution in the synchronization process; the execution state of the timed task is monitored in real time, and if the execution state of the timed task is abnormal, a report is generated and automatic retry is tried. According to the method, the problems of resource waste, data delay, system performance reduction, data conflict loss and the like confronted by third-party cloud service data synchronous processing in the prior art are solved.

According to the heterogeneous memory management system and method oriented to the sparse hybrid expert model, the medium, the program product and the terminal provided by the invention, the interference of cold data on hot data access delay is eliminated by constructing a double-Bank physical isolation architecture in the physical heterogeneous storage module, so that the bandwidth contention of the cold and hot data is avoided; the cold storage unit adopts a low-power-consumption memory and supports a sleep mode, so that near-zero-power-consumption storage of cold data is realized; in the semantic prefetching unit, the prefetching hit rate is increased to 89% by adopting a cosine similarity matching method, so that a dynamic data migration mechanism with a high hit rate is constructed; and the gating collaborative migration engine triggers data migration, and the calculation continuity of the calculation module is guaranteed through DMA control.

The invention relates to the technical field of remote measurement, in particular to a very simple protocol efficient and high-density meter reading method which comprises the following steps: acquiring data frame content, eliminating identity fields, generating a simplified format identifier, constructing a peak shifting scheduling list, detecting sequence consistency, generating a frame supplementing instruction, and dividing synchronous triggering groups to sort meter reading records. According to the method, identity field compression is replaced, frame body space proportion conversion is introduced, data structure content is simplified, a rhythm dislocation sequence is constructed in combination with time migration to achieve high-density node scheduling, frame loss behaviors are screened based on serial number jumping, a frame compensation response task list is automatically constructed, and a synchronous trigger sequence is constructed in combination with time difference judgment. The volume of transmission data is effectively compressed, the utilization rate of channel resources is improved, peak-shifting uploading between nodes is realized to reduce the probability of data collision, overhigh communication load caused by frequent handshake response and multi-level response is avoided, and the continuity, fault tolerance and rhythm collaboration of meter reading scheduling are enhanced.

The invention discloses a knowledge pushing method and system based on a knowledge graph and intention prediction, a terminal and a storage medium. The method comprises the steps that historical document data and new document data of multiple systems are crawled regularly and preprocessed; a triple in the preprocessed data is recognized and stored in a knowledge graph database, updating is suspended and manual auditing is triggered when new and old data conflicts are found, and updating is executed and changes are recorded after auditing is passed; collecting user behavior data, generating a behavior sequence, combining post information of the user, and utilizing the intention prediction model to output a demand probability; extracting associated knowledge according to the demand probability, and sending a knowledge packet link and a brief description to the user through an agent pop-up window; and receiving and storing feedback information of the user on the pushed knowledge packet, and performing system optimization based on the feedback information. According to the method, multi-source heterogeneous knowledge can be automatically integrated, knowledge updating can be monitored and synchronized in real time, knowledge is actively perceived and pushed based on context, and the utilization efficiency of enterprise knowledge is improved.

The invention discloses a bus communication method and system and a storage medium, and the method comprises the steps: carrying out the verification of an address according to a first address field transmitted in a current time period and a second address field received in the current time period when a bus is in an idle state in the current time period; the second address field and the first address field are obtained by the same communication device at the same time; if it is determined that no address conflict exists, data verification is carried out according to the first data field sent in the current time period and the received second data field; the second data field and the first data field are obtained at the same time; and if it is determined that no data conflict exists, obtaining the right to use the bus in the current time period, so as to send the first data field through the bus. According to the invention, the circuit is simple, the hardware overhead is low, the cost is low, and a multi-host communication mode is supported.

The invention discloses a power equipment fault data conflict identification and grading method based on deep learning, and the method comprises the steps: generating a state event based on real-time operation data, determining a dynamic threshold value, and constructing a dynamic activation topological graph structure; constructing a space-time state coding library and performing active state predictive coding; dynamic graph features are extracted through a bidirectional adaptive graph Transform; establishing an attention weight cross-time window comparison sample space, and generating a graph comparison sample pair; performing real-time data conflict code identification on the training feature encoder by using the graph comparison sample; constructing a three-level associated hierarchical topology conflict mode library and updating in real time; and actively matching and outputting a fault conflict grading result in real time by utilizing a grading topology mode library. According to the method, the accuracy and real-time performance of power equipment fault data conflict identification are improved, and the fault studying and judging efficiency and reliability are improved.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses an information conflict detection and data optimization method which comprises the steps of obtaining dialogue information and collecting original data resources, inputting a preset language model to generate an initial response, sequentially completing conflict detection, conflict adjustment, data screening, validity analysis and candidate data weighting by using a multi-discrimination model; and a candidate response set is generated based on the optimized data resources, and a final target response is screened out through logic consistency analysis. According to the method, the multi-layer discrimination model is constructed, data conflict detection, screening and effectiveness analysis are converted into weighted integration, multi-source data resources are systematically optimized, the logic consistency and field applicability of generated content are remarkably improved, and the method is suitable for large-scale popularization and application. The problem of reliability of generated contents caused by data conflicts and stagger quality in the prior art can be effectively solved.

The invention provides a multi-host system based on an IIC bus and a control method, the system comprises M slave devices and N host devices, the host devices and the slave devices are interconnected and communicated through an IIC bus system, each device has an independent communication address, the N host devices are respectively marked as host devices 1-N, and the M slave devices and the N host devices are mutually communicated through the IIC bus system. Wherein the host device 1 has an IIC cycle timing function and is used for determining an IIC host cycle cycle, the host devices 1-N adopt a relay mode to be sequentially configured as a host mode in each IIC host cycle cycle, and the host device in the host mode is sequentially communicated with each slave device; m and N are both greater than 1. According to the invention, a plurality of host devices can work orderly on the IIC bus without time sequence and data conflict, and the method is suitable for aerospace hot backup IIC bus communication systems with high reliability requirements or IIC bus data interaction systems with working requirements of a plurality of host devices.

The invention provides an off-line task autonomy and increment synchronization method and device of a robot and a medium, and belongs to the technical field of robot edge computing control, the method can monitor the network connection state in real time, and when a network disconnection event is detected, system mode switching is triggered; responding to the network disconnection event, switching the system from an online mode to an offline mode, and activating a local task queue; storing the control instruction to a local compression task queue; in the offline mode, the instructions in the local task queue are scheduled to the robot to be executed according to the priorities, and the instructions with the high priorities are executed preferentially; and performing conflict detection and combination on the offline task and the cloud state to complete incremental data synchronization. According to the method, when the network is unstable or interrupted, it is guaranteed that the robot can continuously, safely and efficiently execute tasks; and after the network is recovered, accurate synchronization of the data is realized, and data conflict and loss are avoided.

The invention provides a multi-source data integration method, a storage medium, a program product and electronic equipment, and can be applied to the field of financial science and technology. The method comprises the following steps: calling a corresponding adapter to read original data from each data source according to the types of a plurality of data sources; performing quality evaluation on the original data by adopting a random forest algorithm, determining to-be-cleaned data in the original data, and performing data cleaning on the to-be-cleaned data to obtain cleaned data; standardizing the cleaned data and uncleaned data in the original data by adopting a metadata management technology; under the condition that data conflicts exist in the standardized data, conflicting data are arbitrated so as to determine real data from the conflicting data, and the data conflicts represent that logic conflicts exist in data information from different data sources. The problem that a multi-source data integration scheme in the prior art is low in integration quality is solved.

The invention provides a data synchronization and cache management method and system based on an offline priority architecture, a storage medium and electronic equipment, and the method comprises the steps: intercepting a network request and locally caching target data when the equipment is in an offline state; when the network connection of the equipment is recovered, data synchronization is automatically carried out on the locally cached target data and the server side; based on a version control mechanism, performing conflict detection and solution on a data synchronization process; after data synchronization is completed, periodically checking the validity of locally cached target data based on a cache management mechanism; and based on the update or expiration strategy, according to the validity check result, performing optimization processing on the target data. According to the method, data consistency and integrity are enhanced, data conflicts are automatically detected and solved, data loss or errors are avoided, user experience is improved, data management and storage are more efficient, and better compatibility and cross-platform support are achieved.

The invention requests to protect a multi-machine system synchronization method based on a CXL shared cache consistent memory. Relates to the technical field of high-performance computing and memory interconnection, at present, a plurality of synchronization mechanisms are provided in a Linux system, and the synchronization mechanisms are designed to face a multi-core and multi-process environment of a stand-alone system and are used for guaranteeing concurrent access of a plurality of processes to shared data. However, the action range of an existing synchronization mechanism is limited in a single system, and for the situation that multiple processes belonging to multiple independent host systems concurrently access data in a CXL shared memory, the cross-host concurrent access requirement exceeds the application range of the existing Linux synchronization mechanism, data competition and inconsistent access are possibly caused by direct use, and the data access efficiency is improved. Even if the system crashes, the cross-host access security on the CXL shared memory cannot be ensured. The invention aims to construct a safe and efficient synchronization mechanism oriented to multi-system parallel access CXL shared memory data so as to realize cross-host multi-process synchronous access to the data in the CXL shared memory.

The invention discloses a real-time processing method and system for distributed data streams, and particularly relates to the technical field of distributed data processing, and the method comprises the following steps: collecting multi-source data streams and marking priorities, combining data types and priorities to carry out adaptive segmentation, carrying out load balancing distribution on processing units, and resolving data conflicts; and incremental integration and caching of hotspot data are carried out, and full-link tracing and dynamic tuning are carried out. The system comprises five modules, namely an acquisition labeling module, a segmentation module, a parallel processing module, an integration optimization module and a tracing tuning module. According to the real-time processing method and system for the distributed data flow, priority processing of core data is achieved, data consistency is guaranteed, the resource utilization rate and the system maintainability are improved, and the processing requirements for high real-time performance and high reliability are met.

Embodiments of the present disclosure provide a storage chip and a storage system. The storage chip is configured such that characterization parameters representing the process corner of the storage chip are stored therein, and a reference voltage with an adjustable magnitude is further provided therein. The magnitude of the reference voltage is adjustable based on the characterization parameters, and the storage chip adjusts the delay of data read from a storage unit to output from a data port based on the reference voltage. Embodiments of the present disclosure are beneficial to improving the neatness of data signal transmission and preventing data conflicts.

The invention provides a data synchronization method, a data synchronization device, electronic equipment and a storage medium. The method is applied to an edge device and comprises the steps that a first change state of data in a cloud end and a second change state of the data in the edge device are monitored, a message queue exists between the edge device and the cloud end, and the first change state is obtained by pushing the message queue to the edge device from the cloud end; in response to the update of any one of the first change state and the second change state, triggering the edge device and the cloud to execute a data synchronization task; the execution of the data synchronization task comprises: calling a data query API provided by the cloud, the data query API being configured by the cloud according to synchronization configuration information, and the synchronization configuration information comprising an entity needing to be synchronized between the cloud and the edge device, a data range of the entity and a data conflict resolution strategy; and completing data synchronization between the cloud and the edge device through the data query API.