117 results about "Event list" patented technology

The invention relates to a digital finance and taxation auditing method based on artificial intelligence, and the method comprises the following steps: S1, obtaining electric finance and taxation multi-source data, and carrying out the preprocessing of the data, and obtaining the preprocessed electric finance and taxation multi-source data; s2, constructing a finance and taxation knowledge graph according to the preprocessed power finance and taxation multi-source data; s3, constructing a multi-modal risk detection model, and obtaining a risk event list and a whole-course data traceability path according to the finance and taxation knowledge graph and the real-time electric finance and taxation multi-source data; s4, according to the risk event and traceability, based on a rule model, generating a structured decision instruction set including all key information and traceability links; and S5, converting the structured decision instruction set and the finance and tax knowledge graph into a standard relation graph for input, and dynamically displaying fund flow, risk events, abnormal aggregation and traceability paths among enterprises through D3. Js rendering. According to the invention, the efficiency and reliability of electric power digital finance and taxation auditing are significantly improved.

The invention provides an intelligent data quality monitoring method and system. The method comprises the following steps: performing data processing on multi-source heterogeneous data by utilizing a unified data model; inputting historical data as a training set into the pre-training model for training optimization to obtain an optimized pre-training model, and performing threshold determination on the standardized distribution data stream by using the optimized pre-training model in combination with an adaptive threshold module; inputting the processed abnormal event list into a context awareness and dynamic priority management module to carry out de-duplication optimization transmission; carrying out root analysis on the abnormal event list after the de-weighting optimization by utilizing a root analysis tool; generating a repair strategy for the root analysis result by using the assistance of a repair suggestion engine; and inputting the repair strategy and the visual report into a cross-platform monitoring interface, and generating a repair suggestion and an early warning notification. According to the method, the data consanguinity map is constructed based on the graph database, minute-level traceability of abnormal events is achieved, and the troubleshooting time is shortened by 50%.

The invention relates to the technical field of equipment fault prediction, and discloses a fire fighting equipment fault early warning method and system based on multi-dimensional data linkage, and the method comprises the steps: collecting multi-dimensional operation parameters, and carrying out the data preprocessing, and obtaining standardized data; and then time synchronization and dependency relationship analysis are carried out, an equipment dependency graph is constructed, influence weights among equipment are quantified, and abnormal fluctuation characteristics are extracted to form a risk mode set. And based on the risk mode set, identifying a high-frequency high-weight risk cluster as a preliminary fault feature through grouping analysis, and determining a core fault feature by combining historical data correlation analysis. And then matching abnormal signals to generate spatial labels, integrating data to form an abnormal event candidate list, analyzing an event propagation path in combination with environmental data, and verifying the event propagation path to obtain a final abnormal event list. And finally, performing priority grading according to a historical mode matching result, and generating a visual early warning report by using a three-dimensional point cloud rendering technology. According to the method, the fault early warning accuracy of the fire-fighting equipment is improved.

The invention relates to the technical field of traffic scheduling, in particular to a road traffic analysis scheduling method and system based on event driving. The method comprises the following steps: collecting traffic state data in real time, and generating an original traffic data flow; feature extraction is carried out on the original traffic data flow, a space-time traffic flow graph is constructed, and a dynamic traffic network graph is generated; performing analysis and space-time correlation analysis on the dynamic traffic network diagram to generate a traffic event list; triggering an intelligent scheduling response based on the traffic event list, calling a corresponding scheduling strategy template according to the event type, and generating a candidate scheme set; a multi-objective optimization model is constructed for optimization, and an optimal scheduling scheme is generated; issuing the optimal scheduling scheme to road control equipment, and executing traffic scheduling; and collecting traffic feedback data, evaluating a scheduling effect, and if an expected target is not reached, adjusting scheduling parameters and regenerating an optimization scheme until the traffic state is improved. According to the invention, accurate analysis and efficient scheduling of road traffic can be realized.

The invention provides a logic detection method for game time events and a terminal. The logic detection method comprises the steps that player behavior events and game state change events in a game are captured in real time, and event nodes in the events are recorded to construct a time event dependency graph; according to the time event dependency graph, causal contradictory logic among the events is detected; and performing contradictory severity scoring on the corresponding contradictory events according to the causal contradictory logic, and outputting a contradictory event list with a contradictory severity score. By capturing player behaviors and game state changes in real time, constructing a time event dependency graph and detecting causal contradictions between events, logic contradictions under a time travel mechanism in a game are automatically recognized, the severity of the contradictions is quantified through severity scores, developers are helped to quickly position and repair problems, and the game quality is improved. Compared with traditional manual inspection and static test, the test coverage rate and the detection efficiency are remarkably improved, and the method is suitable for complex time travel narrative games.

The invention discloses a cultural relic three-dimensional dynamic scene display system based on a virtual-real fusion technology, and relates to the technical field of mixed reality, and the system comprises a data collection module which obtains original signals of a to-be-displayed cultural relic and a surrounding environment, and generates an environment feature vector and an environment fusion index; the twinborn simulation module is used for generating health state feature vectors of the cultural relics in combination with finite element grids and carrying out prediction simulation on the deterioration state of cultural relic materials; the model creating module is used for creating a three-tense model resource package and generating time axis metadata by adopting a vertex interpolation and mapping mixing technology; the story layout module is used for constructing an environment event mapping rule base, obtaining a ranked trigger event list through priority ranking, and generating a scene script sequence; according to the method, the health state and the degradation process of the cultural relics under different environmental conditions can be dynamically reflected, and three-dimensional scene display changing along with time evolution is provided.

The embodiment of the invention provides a multi-device cooperative control method and system based on a bus communication protocol, and belongs to the field of multi-device cooperative control of the bus communication protocol. The method comprises the steps of collecting multi-modal data, extracting event data, analyzing event metadata, obtaining an event influence radius and an event type, grading events according to the event influence radius and the event type, and obtaining an event arbitration result through a dynamic arbitration mechanism based on a graded event list. According to the event arbitration result, distributed space-time collaborative decision making is carried out, and a collaborative group execution scheme is obtained; and based on the graded event list, sending the cooperative group execution scheme to corresponding equipment to complete multi-equipment cooperative control. According to the method, event grading is realized through the three-dimensional evaluation matrix, instant response of high-priority events is ensured in combination with a dynamic arbitration mechanism, and the real-time performance and reliability of multi-device collaboration are remarkably improved by adopting a distributed space-time collaborative decision-making system.

The invention relates to the technical field of data processing, and particularly provides an intelligent decision-making method and system for multi-source data fusion, and the method comprises the steps: carrying out the parallel collection of environment data and equipment state data under the same timestamp, obtaining multi-source data, transmitting the multi-source data to a PLC at an equipment end, and carrying out the local preprocessing, performing time sequence feature extraction and anomaly detection on the preprocessed multi-source data to obtain labeled multi-source data and an abnormal event list, and inputting the labeled multi-source data and abnormal event list into a preset weight adjustment model to obtain a dynamically adjusted weight vector; and carrying out weighted fusion on the labeled multi-source data by using the dynamically adjusted weight vector to obtain fused data, and carrying out intelligent decision making based on the fused data. By carrying out dynamic weighted fusion on the environment data and the equipment state data, the overall intelligent regulation and control capability of the system is improved, and the problems that the reliability of multi-source data fusion is insufficient and the weight cannot be adaptively adjusted are solved.

The invention relates to a flood event automatic identification method and system based on frequency domain features and multiple constraint conditions and a medium, and the method comprises the following steps: data preprocessing: obtaining original daily scale hydrological time series data, carrying out missing value detection and interpolation, and generating a flow hydrograph overview map; base flow separation and smoothing; identifying a candidate peak and calculating a threshold value; performing frequency domain analysis and period determination; determining the optimal separation duration; and flood event separation and output: combining and screening candidate flood peaks by applying the optimal separation duration, the valley depth threshold value and the absolutely threshold value of the highlight degree, determining a final flood peak position and event starting and ending time, retaining an event of which the flood peak flow is greater than the average flow in a flood season, and outputting a flood event list and a characteristic statistical result. According to the method, the problems of subjectivity and low efficiency of a traditional method are solved, the adaptation bottleneck of cross-basin application is broken through, and efficient, accurate and automatic identification of flood events in basins with different hydrological characteristics is achieved.

The invention provides a mobile payment transaction behavior analysis method based on spatial data, and the method comprises the steps: obtaining time series data of transaction amounts in different geographic regions, carrying out the feature extraction, and forming a transaction amount fluctuation feature set; correcting a weight value of spatial-temporal heterogeneity according to the fluctuation period, the adjacent region sensitivity and spatial-temporal change characteristics of the inter-region transaction intensity, and determining an adaptive spatial weight matrix; acquiring a historical distribution mode of the potential abnormal region set transaction data, analyzing a deviation degree between the current fluctuation amplitude and the historical mode, judging the authenticity of an abnormal signal, and determining an abnormal event list; and calculating the influence diffusion degree of the abnormal events on the surrounding area to obtain the variance expansion degree, adjusting the abnormal detection parameters according to the abnormal event list, optimizing the detection rule, and determining the spatial dependency relationship network.

A trouble ticket associated with an incident is automatically triggered. A task is initiated to collect system event logs from one or more servers based on the trouble ticket. A system document is obtained that includes an event list. The event list and the system event logs are provided to an Artificial Intelligence (AI) engine for analysis. An AI diagnosis result is generated by the AI engine. The AI diagnosis result is received from the AI engine. A remote action is executed to resolve the incident based on the AI Diagnosis Result. Action result logs are obtained in response to executing the remote action. A result document is generated that includes a result of the executing the remote action. The result document is provided to the AI engine for training a model used by the AI engine to generate the AI diagnosis result.

The present application relates to a kind of EPR nuclear power unit accident initiation event list optimization method and system, method includes: collecting the initiation event list of each nuclear power unit;Each initiation event list is compared and analyzed, and the optimization object of the accident initiation event list of EPR nuclear power unit is determined according to comparison result;Frequency analysis is carried out to the accident initiation event in optimization object;EPR accident classification standard and frequency analysis result are combined to reclassify accident;According to the classification result, optimization initiation event list is carried out;Generation optimized initiation event list.Through implementation of the present application, after the optimization of the accident initiation event list of EPR nuclear power unit, optimization EPR accident analysis and EPR nuclear power unit operation technical specification are carried out, realize unit online maintenance, further improve the economic benefit of nuclear power plant under the premise of guaranteeing safety.

The application provides a kind of intelligent government affair hotline mass appeal analysis, detection method, the method includes the following contents: pull daily work order data regularly;The work order content in work order data is vectorized coding;For vectorized work order data, using DBSCAN clustering algorithm, obtain classification cluster;Traversal classification cluster, utilize the address feature of classification cluster, complaint feature, with the data not included in any cluster, again using DBSCAN clustering algorithm expands classification cluster, for obtaining more accurate complaint quantity and complaint number information;Obtain the complaint summary of each classification cluster through large model;Data is written into data.The application can realize mass appeal detection considering semantics and spatial information, replace the redundancy, repetitive work of original manual statistics in an intelligent way, can effectively help to identify and integrate similar appeals, so as to improve the processing efficiency, optimize the service quality, quickly and efficiently provide daily mass event list.

The invention discloses a nuclear chemical engineering facility safety analysis method and system and electronic equipment, and belongs to the technical field of nuclear chemical plant safety analysis. The analysis method comprises the steps of obtaining an originating event list of the nuclear chemical engineering facility; according to the originating event list and the event sequence logic, respectively constructing an event tree model corresponding to each originating event; a fault tree model of a key fault branch in each event tree model is constructed, and the fault tree model comprises basic events connected with logic gates; calculating a basic event probability based on correlation analysis, human factor reliability analysis and an equipment failure database; and according to each event tree model, the fault tree model and the basic event probability, calculating a safety analysis result corresponding to each originating event. According to the method, the problems that a security analysis method based on a deterministic theory in the prior art is too conservative and low in accuracy can be solved.

The present disclosure relates to an information display method, apparatus, electronic device, and storage medium. The method includes: displaying an activity main page; the activity main page includes an activity list area, the activity list area includes a plurality of activities, and the plurality of activities correspond to multiple activity types; in response to a preset gesture operation based on the activity list area, displaying activity content cards corresponding to each of the plurality of activities; on each activity content card corresponding to an activity, displaying the content multimedia resources of each activity; in response to a trigger operation on any activity content card, displaying an activity page of a target activity corresponding to the any activity content card; the activity page of the target activity includes activity details information of the target activity. The present disclosure can simplify the operation steps for viewing content resources, improve the convenience and intuitiveness of viewing content resources, and enhance the activity attraction.

An apparatus for maintaining an event listing using voice control, comprising at least a processor and a memory containing instructions configuring the at least a processor to receive acoustic data, identify a voice input including event activation data as a function of the received acoustic data using a voice recognition module, wherein the event activation data comprises an identification of a named entity, initialize at least an event data structure associated with the named entity as a function of the event activation data, insert the at least an event data structure into an event listing maintaining a plurality of event data structure, and display the event listing using a user interface.

The invention discloses a universal traffic anti-shake processing method based on distributed cache, and the method specifically comprises the following steps: S1, when an event is accessed, storing or updating an event record in the distributed cache according to an event identifier id; s2, obtaining candidate events from the distributed cache in batches; s3, the candidate events are judged according to the idle time threshold value and the maximum waiting time threshold value; when the event exceeds the idle time threshold value or the maximum waiting time threshold value, adding the event into a to-be-processed event list; s4, before business execution, intercepting a business method by a section and injecting the to-be-processed event list into business processing logic; and S5, after the candidate events obtained in batches are processed, performing security cleaning on the event records which are not updated according to comparison of the latest updating time before and after processing. According to the method, the database writing quantity is greatly reduced, and automatic batch merging processing of high-frequency behaviors is realized.

The invention relates to the field of guardrail topology generation, and particularly discloses a guardrail topological graph generation system based on guardrail connection identification, which comprises the following steps: firstly, acquiring an original signal flow generated by connection or disconnection operation in real time through a sensor deployed at a guardrail connection port; the signals are then parsed into a structured event list. By analyzing the time sequence of the events, the active connection event of one guardrail is matched with the passive connection event of the other guardrail in an extremely short time window, so that the connection relationship between the guardrails is accurately identified. Once the connection relation is confirmed, nodes representing guardrails and edges representing connection are generated on the basis, and a logic topological graph is formed. And finally, performing visualization processing on the logic diagram to generate a visual layout form image. Therefore, the real-time and remote visual supervision of the guardrail topology is realized, and the construction management efficiency and the safety response speed are effectively improved.

The present disclosure provides a hotspot event mining method and device, equipment and medium, relates to the technical field of data processing, and particularly relates to the technical field of big data and artificial intelligence. The implementation scheme is: obtaining a plurality of original documents; for each original document, obtaining at least one keyword included in the original document; based on a plurality of keywords included in each of the plurality of original documents, obtaining at least one keyword frequent item set; based on the at least one keyword frequent item set, determining a plurality of preliminary screening documents from the plurality of original documents; at least based on a plurality of keywords included in each of the plurality of preliminary screening documents, constructing an event graph; based on the event graph, obtaining at least one event cluster; and based on the at least one event cluster, determining a hotspot event list.

The present invention proposes an event library-based simulator simulation method, system, device, and medium, relating to the field of simulation. The method comprises: starting the simulation process of the corresponding module in response to a simulation start signal; inserting received events from different processes into a binary tree event library; traversing the binary tree event library in sequence based on a time wheel stepping process to query node event status; retrieving the corresponding node event based on the query result, analyzing the node event, parsing the corresponding source event instance and destination event instance, and updating the event instance attributes according to a preset parsing protocol; sending the node event to the event instance for processing based on the destination event instance to obtain corresponding event execution status information; and printing the step time, event name, event list, and event execution status information. By optimizing the simulation processing flow, the method can achieve the simulator's clock accuracy requirements and facilitate timing analysis and adjustment.

The invention discloses a personalized tourist route recommendation method based on tourist trust degree, and relates to the technical field of smart tourism, and the method comprises the steps: obtaining tourist data, calculating a real-time deviation value of the tourist trust degree, and generating a trust crisis event list; according to the trust crisis event list, judging whether the tourist has trust crisis events which continuously and densely occur in the travel, and outputting a fusing control message; inputting the fusing control message into a cognitive map generation engine, and establishing a basic trust relationship network; calling path reference data in the trust model parameter library, and performing root cause matching in combination with an attribution template preset in the event attribution knowledge library to generate a visual trust repair report; and performing route correction based on the visual trust repair report. According to the method, the fusing control message is input into the cognitive map generation engine, and the basic trust relationship network is constructed in combination with the historical interaction data, so that the multi-dimensional association between the tourist and the service provider can be systematically presented.

1. Name of the product in this design: Graphical User Interface for Facility Safety Monitoring of Electronic Equipment. 2. Application of this design: This design is intended for use in an electronic device. 3. The key design features of this product are its graphical user interface. 4. The picture or photo that best illustrates the key design points: Design 1 front view. 5. Other views are omitted as they are standard design. 6. Design 1 is designated as the basic design. 7. Purpose of the graphical user interface: The interface is used for monitoring the operational risks of key highway facilities. 8. Human-computer interaction method of graphical user interface: Design 1: The main view of Design 1 is the main interface for monitoring the operation risk of key facilities on highways. In the main view of Design 1, clicking on an event in the event list on the left will display a pop-up window showing the details of the corresponding event. For example, clicking on the last event will take you to the Design 1 interface change state diagram. Design 2: The main view of Design 2 is the main interface for monitoring the operational risks of key highway facilities. In the main view of Design 2, click "Object Management" in the upper right corner of the interface to open the "Object Management" list page and enter the Design 2 interface change status diagram.

Embodiments of the present disclosure relate to malware process detection techniques. A method is presented that includes obtaining, for an identified process from raw data, a list of activities and a list of used resources related to execution of the identified process; generating, for each identified process, a graph representation, wherein the graph representation includes nodes and edges, wherein the nodes are assigned with elements from the list of used resources or an identification value of one of the two identified processes, and wherein the edges are assigned with elements from the list of activities; combining the generated graph representations of the identified processes when the identified processes are linked together, wherein the combination outputs a combined graph representation that is a representation of one of the events to be classified; providing the representation of one of the events to be classified to a classification model.

Disclosed in the present invention are a microservice memory leak monitoring method, system and apparatus, and a storage medium. The method comprises: starting a memory leak monitoring program of a microservice, and loading a first tracepoint probe and a second tracepoint probe, the first tracepoint probe and the second tracepoint probe being set by means of an eBPF program; processing the first tracepoint probe and the second tracepoint probe by means of a map mechanism, so as to obtain an event list, the event list being used for storing process IDs, and memory allocation and memory release events; according to a first process ID of a microservice to be monitored, retrieving from the event list growth data of released memory corresponding to the first process ID; and acquiring memory growth data of said microservice, and, according to a difference value between the memory growth data and the growth data of released memory, determining whether there is a memory leak in said microservice. The embodiments of the present application helps to improve the resource utilization rate of clusters and improve the safety performance of systems, and can be widely applied to the technical field of cloud computing.

The embodiment of the invention discloses a log alarm method and device, electronic equipment, a storage medium and a program, and the method comprises the steps: carrying out the dynamic partitioning of an original collection log according to a log type, and obtaining a partitioned log; performing unified processing on the data structure of each type of partition log through a large model to obtain a structured partition log; key log events of the structured partition logs are automatically recognized through the large model, and a key log event list is obtained; and monitoring the original collection log in real time according to the key log event list, and generating real-time log alarm information. According to the technical scheme provided by the embodiment of the invention, the log alarm processing efficiency, the automation degree and the self-adaptability can be improved.

The invention belongs to the technical field of public safety emergency management and control and Internet of Things fusion, and discloses a park public safety comprehensive management and control system based on the Internet of Things. Comprising a data acquisition module used for acquiring user event description information and campus Internet of Things equipment data in real time; the event processing and verification module is used for carrying out association analysis on the event list and campus Internet of Things data, obtaining event clusters containing credibility scores and determining the situation level of each event cluster by constructing a level decision tree, and the resource scheduling and guarantee module is used for triggering a network resource scheduling process according to the situation level of each event cluster. Dynamically creating an emergency network slice instance based on the generated resource scheduling request command, performing exclusive network resource allocation based on the emergency network slice instance, and outputting resource allocation completion confirmation; and the emergency response and monitoring module is used for confirming and executing response operation based on resource allocation, continuously monitoring the progress of the reported event and outputting a response execution report.

The application provides a mobile payment transaction behavior analysis method based on spatial data, comprising: acquiring time series data of transaction amounts in different geographical regions, performing feature extraction, and forming a transaction amount fluctuation feature set; according to the fluctuation period and the sensitivity of adjacent regions, correcting the weight value of the spatio-temporal heterogeneity according to the spatio-temporal change characteristics of the transaction intensity between regions, and determining an adaptive spatial weight matrix; acquiring the historical distribution mode of the transaction data of the potential abnormal region set, analyzing the deviation degree of the current fluctuation amplitude from the historical mode, judging the authenticity of the abnormal signal, and determining an abnormal event list; calculating the variance expansion degree of the influence diffusion degree of the abnormal event on the surrounding region, adjusting the abnormal detection parameters according to the abnormal event list, optimizing the detection rules, and determining a spatial dependence relationship network.

The invention discloses a technical field subversive potential prediction method and device and a program product, and the method comprises the steps: firstly obtaining patent data of a target technical field, and constructing an IPC classification set for the patent data in each preset time window; constructing a patent technology classification bipartite graph according to the association relationship between the patents in the classification set and the IPC classification numbers; based on the co-occurrence strength of any two technology classification nodes in the bipartite graph, generating a technology classification co-occurrence network; performing community division on technical classification nodes in the technical classification co-occurrence network; performing cross-time window community similarity calculation on community division results in different time windows, and constructing a community evolution event list; and finally, obtaining a subversive potential index of the target technical field according to the community evolution event list, and obtaining the subversive potential index of the target technical field based on the subversive potential index. According to the embodiment of the invention, the accuracy of subversive potential prediction in the technical field is effectively improved.

The embodiment of the invention discloses an urban user event-oriented resource scheduling method and device based on big data. A specific embodiment of the method comprises the following steps: preprocessing a real-time event data stream, a preset assessment rule base and a historical event database to obtain a preprocessed data set; performing deep semantic analysis and multi-label classification processing on the preprocessed data set to generate semantic understanding information; performing multi-dimensional elimination judgment and resource demand mapping processing on the semantic understanding information to generate event property and resource demand information; generating an effective governance event list based on the event property and the resource demand information, and constructing a corresponding resource demand thermodynamic diagram based on the effective governance event list; generating a dynamic resource allocation instruction set; and scheduling the corresponding cross-modal resources according to the dynamic resource allocation instruction set. According to the embodiment, accurate resource scheduling and efficient cross-modal resource configuration in the urban user event treatment process can be realized, and the time cost of event treatment is reduced.