53 results about "Event model" patented technology

The invention discloses a sales resource distribution system based on a dynamic customer portrait, and relates to the technical field of artificial intelligence and big data application, and the system comprises an event modeling module, an abnormity monitoring module, a copy management module, a trial investment evaluation module, an unfreezing control module and an income backflow module. According to the method, a distribution offset map is generated by playing back customer behavior data in historical burst periods, and customer groups and key interaction contacts with easily distorted behaviors are identified as data monitoring references. According to the invention, through dynamic monitoring, label copy management, trial investment feedback evaluation, segmented unfreezing control and a negative pressure backflow mechanism, accurate identification and verification recovery of customer behavior abnormity are realized, the label stability is guaranteed, the sales resource distribution is dynamically optimized, and the response capability and configuration efficiency in an emergent environment are improved.

The invention relates to a progressive memory delay monitoring and diagnosis method oriented to a virtual memory subsystem. The method comprises the following steps: mounting a BPF program to a plurality of key event points on a kernel; when the key event point is triggered, acquiring state information of a corresponding event; packaging the state information into an event, and writing the event into a perf ring buffer associated with the outputmap; and the user mode program asynchronously reads the packaged event from the perf ring buffer, performs classification and aggregation according to the process and the event type, generates a delay terminal log and a histogram, and outputs a diagnosis result. Through systematic architecture design, the state keeping capability and the kernel context access capability of the eBPF are combined with an event model of a virtual memory subsystem, and a set of closed-loop monitoring system oriented to a diagnosis target is constructed. High-precision and high-reliability memory operation delay measurement is realized.

A vehicle device may be configured to execute one or more event models, such as based on input from one or more of the audio capture devices, image capture devices, and / or other sensors associated with the vehicle device, to intelligently detect safety events, such as unsignaled lane departures, in real-time. Detection of a safety event may trigger an in-vehicle alert to make the driver aware of the safety risk. The vehicle device may include logic for determining which asset data to transmit to a backend server in response to detection of a safety event, as well as which asset data to transmit to the backend server in response to analysis of sensor data that did not trigger a safety event. The asset data transmitted to the backend server may be further analyzed to determine if any action should be taken by the user of the backend server.

The invention discloses a data burying point and analysis method and system for cross-platform dynamic configuration, and relates to the technical field of data burying point, a server determines a candidate parameter set of burying point configuration based on an event model, performs optimization through a swarm intelligence algorithm, generates dynamic burying point configuration including a target control topological neighborhood feature vector, and transmits the dynamic burying point configuration to a server; issuing to a terminal; the terminal calculates the geometric structure similarity between view tree nodes and topological neighborhood feature vectors, and binds the nodes exceeding a threshold value as a buried point trigger source; when a burying point trigger source is activated, obtaining an operation sequence of a current context and sampling strategy generation event data, injecting a logic precursor identifier and a statistical weight factor, and sending the data to a server through local caching and batch reporting; and the server performs logic causal rearrangement, constructs a statistical analysis model to identify a statistical weight factor, executes inverse probability weighted calculation and outputs an unbiased analysis result, so that the problem of burying point failure caused by version iteration is solved, and the robustness and adaptability of burying point configuration are improved.

The invention discloses an intelligent low-carbon service model and method based on block chain fusion, particularly relates to the technical field of low-carbon management, and is used for solving the problem that the credible recognition and settlement of carbon behaviors are not clear. According to the method, identity verification, time marking and caliber standardization are carried out on energy consumption and travel multi-source data through a trusted data gateway, a carbon behavior voucher containing a signature and an abstract is generated, minimum disclosure under an index upper chain and an original text chain is adopted, it is ensured that the source and the caliber are verifiable and cannot be tampered, and then merging is carried out through a unified event model; and performing conflict resolution and consistency verification to form a one-event one-key event, attaching a consistency label and a credibility index, performing calculation by a rule base and a scene parameter set, performing intelligent contract accounting, and providing rollback correction by using a unique identifier of the event, enabling the credibility index to participate in integral and right confirmation, performing low-credibility entering and re-verification, and suppressing abnormities. And the fusion accuracy and the auditing efficiency are improved.

An integrated artificial intelligence camera system provides multi-domain monitoring and enterprise automation from a single hardware endpoint. A camera assembly and auxiliary sensors, including at least one of depth, thermal, audio and environmental sensors, feed an edge compute module executing modular perception, identity, physiological estimation and domain-logic pipelines. The system detects and tracks persons, objects and activities; generates pseudonymous identity tokens for enrolled workers; estimates breathing rate and related wellness indicators from non-contact visual and thermal signals; and transforms these outputs into normalized event records annotated with security, inventory, workforce, payroll, physiological and compliance labels. A unified event model standardizes timestamps, device identifiers, site and zone identifiers, actor identifiers, metrics, confidence scores, policy tags and evidence references, enabling direct integration with payroll, inventory management, security incident and analytics platforms. A policy engine governs feature activation, anonymization and retention per jurisdiction and user role.

The invention discloses a multi-agent construction method for fault handling of a high-voltage converter station, and relates to the technical field of electric power automation, and the method comprises the following steps: S1, mapping establishment of in-station equipment and agents; s2, constructing a unified identifier and event model; s3, organization and credibility calibration of evidence information; s4, performing consistency arbitration and conflict grading processing; s5, arranging and executing a fault disposal process; s6, running experience learning and rule self-evolution; and S7, auditing and tracing the disposal process. According to the method, a multi-agent construction mechanism is introduced into the converter station, devices such as a direct current pole, a valve tower, protection, measurement and control, operation and the like are respectively mapped into independent agents, and cross-domain cooperation is realized under a unified identification and event model; each agent not only has an autonomous information processing capability, but also can realize rapid fusion and consistency judgment of multi-source information through an evidence chain and an arbitration mechanism, thereby forming explainable and traceable disposal suggestions when a fault occurs.

A model management system for validating models for predicting a client behavior event includes a model validation system configured to execute each of multiple stages of a selected model, which includes calculating a respective output based on a respective input of each of the stages. The model validation system is configured to separately verify, based on the respective outputs, each of the stages. The model validation system is configured to generate and store model data corresponding to the respective outputs of each of the stages. The model data includes a first set of model data and a second set of model data different from the first set of model data. A user interface module is configured to receive an indication of credentials of a user and selectively retrieve and display one of the first set of model data and the second set of model data based on the indication.

A method of identifying events within a wellbore comprises obtaining a first set of measurements of a first signal within a wellbore, identifying one or more events within the wellbore using the first set of measurements, obtaining a second set of measurements of a second signal within the wellbore, wherein the first signal and the second signal represent different physical measurements, training one or more event models using the second set of measurements and the identification of the one or more events as inputs, and using the one or more event models to identify at least one additional event within the wellbore.

A system is provided for determining an asset cleaning schedule. In some embodiments, the system may include a plurality of sensors tuned to monitor the asset, and a computing system, the computing system including at least one data processor and memory for storing instructions, the instructions causing the at least one data processor to perform an action when executed by the at least one data processor. In some embodiments, the actions performed by the processor may include receiving data from the plurality of sensors characterizing the asset's operational efficiency, determining the asset's operational efficiency, determining an operational efficiency threshold characterizing undesirable operational efficiency, determining an asset cleaning schedule based on the asset's operational efficiency and the operational efficiency threshold using an optimization algorithm, and providing the cleaning schedule.

The invention relates to a system for realizing transaction gateway distribution based on an asynchronous event model, and the system comprises an SDK access module which carries out the timeout judgment of a transaction request, and receives an asynchronous callback message response; the gateway access module is used for receiving the transaction request and decompressing the data; the service conversion module is used for loading service conversion rules from the service conversion management module and carrying out logic conversion and judgment on the request data; the data storage module is used for storing the business conversion rule and the effective time range thereof; and the service conversion management module provides addition, deletion, modification and check functions of service conversion rules. The system for realizing transaction gateway distribution based on the asynchronous event model has high availability, accesses the server through the SDK access module, realizes background service detection through the heartbeat detection module, realizes automatic switching when a fault is found, and ensures high availability of the service; according to the invention, the method is high in business rule taking-into-effect real-time performance, and has the obvious characteristics of high business rule taking-into-effect real-time performance, high expansibility, high availability and the like.

This application discloses a modeling method, apparatus, and equipment for a flight early warning center, relating to the field of civil aviation early warning technology, and is used to solve the technical problems of poor early warning accuracy, consistency, and centralized control capabilities in existing technologies. The method includes: constructing a rule management center using dynamic rule management services and dynamic rule loading services; the rule management center having standardized early warning event models and early warning rule distribution protocols; constructing a dynamic early warning rule library and an early warning processing center using the Drools rule engine; constructing an early warning calculation center using the Drools rule engine and the Disruptor asynchronous processing framework; and constructing a flight early warning center based on the dynamic early warning rule library, rule management center, early warning processing center, and early warning calculation center. Therefore, this application can effectively improve early warning accuracy and consistency through "Drools rule engine, Disruptor asynchronous processing framework, standardized early warning event models, and early warning rule distribution protocols."

The invention relates to the technical field of evaluation optimization, and discloses an advertisement delivery data evaluation system based on multi-channel information integration, and the system comprises a data standardization and fusion module which is responsible for receiving multi-source heterogeneous original data, carrying out the cleaning through a built-in data connector and an analysis engine, and carrying out the analysis of the multi-source heterogeneous original data; and forcibly converting all data into a unified atomic event model containing a unique device identifier, a standard timestamp and standard latitude and longitude coordinates. The technical effects of scientifically stripping interference factors and quantifying an online conversion net contribution value brought by offline advertisement putting in a causal inference mode are achieved by constructing an exposure group, generating a scientific control group by applying a tendency score matching algorithm and finally calculating a conversion improvement rate; the defect that the actual contribution of offline advertisements to online conversion cannot be accurately attributed and quantified due to the lack of reliable cross-screen tracking and scientific attribution methods is overcome.

The invention relates to an enterprise information security management method, system and device and a medium. The method comprises the following steps: acquiring heterogeneous security data of a physical environment and a network environment, and performing standardized analysis and element extraction on the heterogeneous security data to obtain a physical event and a network event; based on a preset unified event model, carrying out cross-domain association analysis on the physical event and the network event, and calculating space-time proximity and semantic correlation between the physical event and the network event to obtain an association candidate pair set; inputting the associated candidate pair set into a pre-trained causal inference model to obtain the causal intensity of the influence of the physical event on the network event, and identifying the associated candidate pair of which the causal intensity exceeds a preset threshold value from the associated candidate pair set as a cross-domain event pair to obtain a visual attribution map; and triggering an enterprise dual prevention mechanism to perform linkage response based on the visual attribution map. By adopting the method, the overall capability of active defense and risk management and control of an enterprise can be improved.

The invention discloses a traceable graph construction method based on human-multi-agent collaborative software development, and relates to the technical field of software engineering, and the method specifically comprises the steps: defining a traceable graph framework used for representing the full life cycle of software development; collecting events generated by multiple agents and manual developers in the full life cycle of software development, and normalizing the events into a preset event model; analyzing the preset event model, and creating and updating a corresponding node in the traceable atlas; identifying an evolution relationship of a code entity of software development through static analysis on the basis of a scene, and adjusting the consistency of a tracing relationship between nodes and edges in the traceable atlas on the basis of an identification result; a structured graph query interface and a natural language query interface are provided through the traceable atlas, the problem that event semantics between heterogeneous systems are inconsistent can be solved, an enhanced updating mechanism is provided to guarantee real-time performance and accuracy of the atlas, and the risk of information lag is reduced.

The application relates to the field of evaluation optimization, and discloses an advertisement putting data evaluation system based on multi-channel information integration, which comprises a data standardization and fusion module, which is responsible for receiving multi-source heterogeneous original data, cleaning through an embedded data connector and an analysis engine, and forcibly converting all the data into a unified atomic event model containing a unique device identifier, a standard time stamp and a standard latitude and longitude coordinate. A scientific control group is generated by constructing an exposure group and using a propensity score matching algorithm, and finally, a conversion promotion rate is calculated, so that the technical effect of scientifically stripping interference factors and quantifying the online conversion net contribution value brought by offline advertisement putting in a cause-effect inference manner is achieved, and the problem that offline advertisement actual contribution to online conversion cannot be accurately attributed and quantified due to the lack of reliable cross-screen tracking and scientific attribution methods is solved.

The invention discloses a state machine graphical modeling packaging method and device, equipment and a storage medium. The method comprises the steps of obtaining an event description file of a to-be-modeled encapsulation event implementation logic; performing logic analysis on the event description file, extracting a state machine structure, and obtaining hierarchical nesting information corresponding to a finite state machine in the event description file; according to the hierarchical nested information, plane view modeling processing is carried out, a state view model corresponding to a finite state machine in the event description file is obtained, and the state view model displays display information of all event states in a plane display mode; and performing graphic packaging processing on the sub-state machine in the state view model to obtain an event modeling packaging view corresponding to the to-be-modeled packaging event. According to the technical scheme, multi-layer nested state machine graph modeling can be realized, the complexity of the model is effectively reduced, and the readability and maintainability of the model are improved.

The application discloses a method, device and server for dynamically monitoring a track. The method comprises: collecting position information of a mobile terminal in real time to obtain track information of the mobile terminal; obtaining electronic fence data sent by a management terminal to obtain dynamic electronic fence information; fusing the track information and the dynamic electronic fence information to obtain a data stream; inputting the data stream into a strict continuous event model to obtain an abnormality judgment result, the strict continuous event model comprising a condition for triggering an alarm event; and sending alarm information to the management terminal in the case that the abnormality judgment result is that the data stream satisfies the condition for triggering the alarm event. Thus, the transportation or after-sales service of the engineering machinery vehicle is monitored in real time, the construction process is effectively supervised, and the transportation efficiency or the after-sales service efficiency of the engineering machinery vehicle is improved.

The invention relates to the technical field of distributed systems, in particular to a distributed communication system and method based on a multi-protocol message bus, and aims at realizing an intelligent message routing mechanism and providing a unified theme management scheme by constructing a unified event model and designing a pluggable protocol adaptation layer. The problems of complex integration, non-uniform interfaces and poor expansibility caused by heterogeneity of various message protocols in an existing distributed system are effectively solved. Various message protocols such as MQTT, Kafka and RabbitMQ can be seamlessly integrated, a uniform programming interface and consistent message processing experience are provided for upper-layer applications, the complexity and development and maintenance cost of system integration are remarkably reduced, meanwhile, dynamic extension of a new protocol is supported through a plug-in architecture, the flexibility and maintainability of the system are enhanced, and the system is suitable for application and popularization. And finally, simplification, unification and high efficiency of distributed communication are realized.

Implementations of the present disclosure relate to methods, devices, and computer program products for event processing. In the method, first data associated with a first time window is obtained, the first data comprising a first object and a first group of events that are related to the first object. Second data associated with a second time window is obtained, the second data comprising a second object and a second group of events that are related to the second object, the second time window being different from the first time window. An event model describing an association relationship between an object and an event that is related to the object is determined based on the first and second data. With these implementations, multiple time windows are used in determining the event model, and thus the event model may have better performance in accuracy and immediacy aspects.

This application relates to the field of smart grid technology and discloses a distribution network fault location system and method. The system includes a causal generation module, an event inversion module, a dynamic pruning module, a causal co-verification module, and a metacognitive analysis module. The method iteratively calls the causal generation module through the event inversion module to solve for the optimal event parameters containing the fault location, and uses the dynamic pruning module to eliminate physically unreasonable search spaces during the iteration. Then, the causal co-verification module verifies the results and calculates the diagnostic confidence. When the confidence is below a threshold, the event model is upgraded to reconstruct complex faults. Furthermore, the system can generate a diagnosticability map offline to identify diagnostic blind spots. This invention, through generative inversion and model upgrade mechanisms, achieves precise fault location and accurate reconstruction of complex accident sequences, and possesses the ability to quantitatively evaluate its own diagnostic capabilities, significantly improving the intelligence level of fault handling.

One or more touch input signals can be obtained from a touch sensitive device. A touch event model can be used to determine touch and / or gesture events based on the touch input signals. The touch and gesture events can be associated with touch input signals generated from different regions of a web page displayed on the touch sensitive device. Access can be provided to at least one touch or gesture event through a programming interface.

The invention relates to a competition information generation method and device based on a large model, equipment, a storage medium and a program product. The method comprises the following steps: receiving a model processing instruction sent by terminal equipment, wherein the model processing instruction comprises identification information of a target object for triggering the model processing instruction and at least one model operation indicated by the model processing instruction; at least one model operation is executed on a to-be-adjusted competition model corresponding to the identification information of the target object, an adjusted competition model is obtained, and the competition model is a machine learning model created by the target object under the subject category of the current competition; using the trained target prediction model to predict the adjusted match model to obtain prediction data of the adjusted match model; and according to the prediction data and the historical competition data of the target object, generating competition information of the target object in the current competition. By adopting the method, the generation speed of the competition information can be improved.

The invention discloses an intelligent access permission management system based on digital twinning, which relates to the technical field of intelligent access management and specifically comprises the following modules: a data acquisition and processing module, a digital twinning layering module, a knowledge graph construction module, a layering autonomous decision module and an abnormal response closed-loop module. Acquiring an original data stream of the entrance guard and preprocessing the original data stream; defining four types of entity twin object models, constructing independent micro-services and dividing respective service responsibilities; constructing a knowledge graph, mapping entities of the unified event model to nodes of the knowledge graph, mapping identifiers of twin objects into semantic connection between the nodes, storing fact information and recording an evolution track according to an event sequence; three types of autonomous levels are defined for collaboration, and a decision assembly line is constructed for permission judgment and risk assessment; and on the basis of event fusion, an abnormal mode is identified through abnormal detection, high-risk, medium-risk and low-risk events are processed according to predefined responses, and comprehensive automation and intelligentization of access control authority management are realized.

The application belongs to the technical field of cloud computing operation and maintenance, and particularly relates to an alarm intelligent root cause analysis and self-recovery method for guaranteeing the continuity of a legal service platform, comprising the following steps: receiving heterogeneous alarms and performing standardized processing to generate a standard event model; based on feature fields in the standard event model, matching is performed in a preset routing rule library to determine a target analysis module; multi-dimensional diagnostic data associated with the standard event model is collected through the target analysis module, root cause reasoning is performed using a probabilistic graph model, a diagnostic conclusion with a confidence score and a candidate self-recovery strategy are generated; pre-checking is performed according to the risk level of the candidate self-recovery strategy and a security strategy library, if the checking passes, an execution instruction is generated, and if the checking fails, an artificial review process is triggered; the execution instruction is executed and the result is fed back to a knowledge base optimization model and a rule. The application can solve the problems of slow alarm response, difficult experience sedimentation and high operation risk.

The application discloses an intelligent data stream processing system based on Flink and an implementation method thereof, and belongs to the technical field of distributed stream data processing, and comprises the following steps: a data source access layer is used for uniformly accessing multi-source data; an entity monitoring layer is used for capturing business entity changes based on JPA in a non-invasive manner, generating a standardized message body and asynchronously delivering the standardized message body to a double channel; a unified event model layer is used for mapping the standardized message body into a standardized event and expanding the standardized event; an Flink stream processing engine layer is used for complex event processing, state management and window calculation, and supports declarative pipeline definition and dynamic construction; an exception detection layer is used for multi-dimensional exception detection; a distributed task scheduling layer is used for scheduling tasks according to a DAG model, and load balancing is realized through hot spot splitting and state migration; and a result storage and visualization layer is used for storing data by adopting a hot and cold separation strategy and providing a dynamic visualization interface. The application significantly improves the real-time performance, consistency and intelligent level of data processing, and reduces development and maintenance costs.

The invention discloses a client loyalty and right dynamic adjustment realization method based on a telecommunication BSS system, and relates to the technical field of resource evaluation. Comprising the following steps: step 1, based on a telecommunication BSS system, collecting customer behavior data, designing a general event model, defining a behavior event type according to the general event model, storing a behavior event, verifying the behavior event, storing the behavior event for future reference if the verification is passed, and rejecting duplicate events; 2, an integral calculation engine is used for configuring integral rules and dynamically calculating integral, 3, a grade layering model is constructed, a corresponding evaluation rule is defined for each grade, and grade rapid evaluation is triggered according to an evaluation triggering mechanism, and 4, a right and interest matching mechanism is defined; 5, multi-channel display and real-time linkage of related service systems are carried out; and step 6, creating a life cycle model, defining loyalty life cycles of the customer by using the life cycle model, including a new network access period, an active period, a stable period, a silence period, a loss period and a regression period, and matching different incentive measures according to the loyalty life cycles of the customer.

The invention relates to a user behavior burying point and analysis method based on event driving, and the method comprises the following steps: designing an atomic event, a combined event and a composite event as hierarchical event models, determining the identification parameter of each event, classifying each event into a key event, a non-core event and a basic behavior, performing different burying points on each event according to the type of the event to obtain an original behavior data set acquired by mixed burying points; associating the identification parameters of the original behavior data set to the same identification parameters through a matching algorithm, and adopting the original behavior data set after Kafka buffer association to obtain a structured behavior data set after unified identity association; and analyzing the structured behavior data set from multiple dimensions to obtain user behavior characteristics and product experience, and providing differentiated guidance based on the user behavior characteristics and the product experience. Compared with the prior art, the method has the advantages of shortening the service demand response time and the like.

According to embodiments of the present disclosure, a method, an apparatus, a device, and a storage medium for providing content in an application are provided. In a method, a first-type interaction event between a user of an application and content provided in the application is received. Based on the first-type interaction event and an event model, a prediction of whether the user performs a second-type interaction event associated with the content is determined, the event model describing an association relationship between the first-type interaction event performed by the user and the second-type interaction event performed by the user. A provision action of providing the content in the application is adjusted based on the prediction. In this way, the prediction of the second-type interaction event may be determined in a more real-time and accurate manner, and the provision action may be adjusted based on the prediction.