149 results about "Business rule" patented technology

This invention provides an automatic report generation method based on business rules and regular expression matching, belonging to the field of data processing and report generation technology. The method includes: S1. Report requirement parsing; S2. Business rule definition; S3. Regular expression matching rule configuration; S4. Raw data acquisition; S5. Raw data preprocessing; S6. Business rule execution; S7. Regular expression matching validation and field extraction; S8. Report template generation; S9. Report data filling and generation; S10. Report validation and feedback optimization. This invention achieves accurate, automated, and flexible report generation through multi-stage collaboration and multi-algorithm integration.

This invention relates to the field of information review and management technology, and discloses a dynamic approval management system for work order video uploads, comprising: a video upload module, a deep model prediction module, a knowledge graph inference engine, a dynamic rule conflict detection module, a manual review workbench, a blockchain evidence storage module, a two-way anchoring module, and a change warning module; the video upload module is used to receive videos associated with work orders; the deep model prediction module is used to identify preset violations frame by frame in the video and output pre-review tags, confidence levels, and heatmaps of suspicious areas. This dynamic approval management system for work order video uploads, through parallel verification of deep model prediction and knowledge graph inference engines and dynamic conflict detection, can automatically identify suspicious videos whose model output is inconsistent with business rules and generate suspicious tags with causal chains, guiding accurate manual review and significantly reducing the workload of ineffective reviews.

This invention relates to the field of computer software technology and discloses a state-aware dynamic execution link generation and adjustment method. The method first receives a list of sub-intents decomposed from business intents, matches optimal execution resources for each sub-intent using cosine similarity calculation, and monitors the health status of resources in real time for hierarchical classification. Subsequently, based on sub-intent dependencies, matching resource status, and business rules, an improved greedy algorithm is used to generate an initial execution link in a hybrid serial-parallel manner. During execution, changes in resources, rules, and data are monitored in real time. Once a triggering condition is met, an impact range analysis algorithm is used to locate affected nodes, performing resource re-matching and link replanning only locally, and triggering a three-level service degradation strategy. This invention achieves dynamic link optimization and rapid fault tolerance, improving system execution efficiency and robustness.

The invention discloses a building supply chain transparent communication system and method based on a block chain, and relates to the field of block chain technology and building supply chain management, and the system comprises the following components: a block chain underlying network, an intelligent contract module, a terminal collection node, an authority management module and a communication interaction module. According to the invention, by deploying the intelligent contract module, the business rules of automatic payment, performance verification and dispute early warning are realized, and the application of a dynamic acceptance weight verification algorithm and a dynamic threshold dispute early warning mechanism enables the payment trigger logic to better meet the actual demand of a project, improves the payment accuracy by 27%, reduces disputes caused by fuzzy acceptance standards, and improves the payment efficiency. Meanwhile, the dispute early warning mechanism monitors on-chain performance data in real time, automatically triggers early warning when the data deviates from a preset threshold value, synchronously pushes early warning information to related nodes, and generates an on-chain early warning certificate.

This application relates to a method and related equipment for constructing and executing end-to-end processes based on standardized components. The method includes: acquiring process design data for an end-to-end process project of a power company, which includes value stages, key business activities, atomic operation sequences, operation subjects, and outputs; encapsulating atomic operations into standardized components, configuring execution roles for them, reserving element slots, and storing them in a process component library; responding to orchestration instructions, selecting multiple components corresponding to the target business scenario from the component library, establishing control flow logic between components, generating an end-to-end process model, and establishing metadata association relationships between each component and execution roles, digital systems, business rules, business forms, and institutional standards; and deploying the model and metadata associations to a process execution platform. This application improves the construction efficiency, component reusability, and executability of end-to-end processes.

The application discloses a real-time dynamic packing optimization method and system for high hybrid SKU, relates to the technical field of logistics management, and comprises the following steps: acquiring a loading task and a current packing state; analyzing field-specific language business rules to generate executable constraint functions, graph construction metadata and arbitration metadata; constructing constraint dependency graphs, geometric graphs and heterogeneous state graphs; updating the heterogeneous state graph when an order is changed or a container is changed, and determining an influence domain based on logical association and geometric adjacency; inputting the updated heterogeneous state graph into a constraint-aware graph neural network to output a priority score and a position preference vector; generating an action set in the influence domain, pruning and locally re-optimizing to obtain an updated packing scheme. The scheme realizes rule structured expression, incremental solution of the influence domain and local rapid repair, reduces the dynamic rearrangement calculation amount and response time delay, and improves the packing compliance, stability and loading rate.

The application discloses a management platform system for supply chain finance and a non-sensing upgrade method thereof, has the effects of local pilot, small flow verification, automatic observation, rapid rollback, and protects the consistency of in-transit instances and the continuity of key transactions. The system comprises: an infrastructure layer, which provides process arrangement, rule and model execution, event driving, configuration management, task compensation, security authentication and full-link observability, supports the non-sensing upgrade core mechanism including multi-version parallel running, shadow verification, gray release and automatic rollback of the upper-layer business, an interaction layer, which provides unified authentication, permission and configurable menu, supports displaying differentiated functions according to organizations / roles, a domain service layer, which is used for encapsulating business logic operations in the platform, coordinating multiple parties to complete cross-entity transactional tasks, and ensuring the consistency and integrity of business rules, and a fund and channel adaptation layer, which abstracts multiple protocols by using a contract / interface definition language, automatically generates basic adapters, and unifies strategies.

The application provides a large language model data mining interaction method and system based on traceable thinking chains, relates to the cross field of language model technology and ship industry capability data mining, and comprises the following steps: obtaining a data mining demand of a user and generating a thinking chain; monitoring a reasoning node of the thinking chain in real time and triggering a plug-in mechanism and user interaction when necessary; when the result is not as expected, locating a problem node through full-link tracing; and rolling back the thinking chain to the problem node and regenerating an execution link. The application improves the accuracy, interpretability and human-computer interaction efficiency of ship industry capability data mining, and enhances the adaptability of the system to complex business rules and exclusive knowledge in the ship field.

This invention relates to the field of internet data processing technology, and discloses a method and system for dynamic display and price calculation of electronic bidding and tendering. The method includes: responding to the business rule control instructions of the tendering party to generate a switch state vector containing multiple function switch states; when the bidding page is loaded on the bidder's terminal, determining the display and interaction attributes of the input components based on the switch state vector, and controlling the input of bidding data; receiving bidding data containing the original bid value, payment method, and delivery mode, and performing validity cleaning on the data based on the switch state vector; calculating financial cost correction items and logistics cost correction items by combining preset interest subsidy rates and freight parameters; and finally generating the final bid price based on the original bid value and each correction item. This invention achieves the unification of front-end interaction and back-end logic through parameterized control, quantifies non-cash payments and delivery changes as cost corrections, and stores the bid price and settlement price separately.

This invention discloses a data anomaly identification and intelligent completion method, belonging to the field of computer data processing technology. The method includes: data preprocessing; parsing, cleaning, standardizing, and attention-fusion dimensionality reduction of multi-source heterogeneous data; fusion model construction; constructing a three-dimensional sub-model and a dynamic attention fusion layer; multimodal anomaly identification and classification; outputting anomaly confidence and classifying anomaly types through the fusion model; collaborative intelligent completion, processing anomaly data hierarchically based on confidence, and generating completion results through multiple iterations using an improved Transformer model to fuse business rule masks; completion verification and model updating; after dual verification by business logic and data consistency, the model is fine-tuned using incremental qualified data. This invention improves the accuracy of anomaly identification and the rationality of completion, achieves collaborative optimization of identification and completion, adapts to multiple industry scenarios, meets real-time requirements, and can be widely applied to data governance in e-commerce, finance, and other fields.

This application relates to a method, system, device, and medium for real-time evaluation of business rules based on a large language model. The method includes: invoking a large language model to convert natural language business rules into structured description data containing entity identifiers, attribute identifiers, and rule constraints; mapping entity identifiers and attribute identifiers to the location information of corresponding program elements in a domain model based on a pre-stored mapping library, generating detailed mapping data; generating source code files implementing a preset evaluator interface based on the structured description data and the detailed mapping data; converting the source code files into an executable form and executing them in an isolated execution environment; invoking the evaluator interface, evaluating the execution results using generated test cases, and generating a verification report. This application achieves fully automated conversion of business rules to executable code, reducing maintenance costs and improving the efficiency of rule deployment.

This invention provides a human-machine collaborative method and system for short- and medium-term hydrological forecasting enhanced by a large language model, relating to the fields of hydrological forecasting and artificial intelligence. The method includes the following steps: constructing a hydrological forecasting knowledge base for the target watershed; obtaining natural language forecasting requirements and generating structured forecasting task descriptions; recommending solutions and completing parameters based on the knowledge base; executing business rule constraints and verifying solutions; calling the short- and medium-term hydrological forecasting system to perform forecast calculations; and intelligently interpreting forecast results and accumulating experience. The system includes six modules: user interaction, large language model interaction, hydrological forecasting knowledge base, business rule engine, system interface calls, data storage, and logs. Without changing the core architecture of existing short- and medium-term hydrological forecasting systems, this invention introduces a large language model to achieve semantic parsing of forecasting tasks, intelligent construction of forecasting solutions, and intelligent interpretation of forecast results, lowering the system's usage threshold and improving the interpretability of forecast results and the structured reusability of forecasting experience.

This invention discloses an intelligent meteorological data processing system, comprising: a meteorological data parsing and storage subsystem, which implements two-phase commit based on Kafka middleware for receiving and parsing multi-source heterogeneous meteorological data; a business configuration subsystem, which provides a rule configuration interface for dynamically configuring meteorological data processing rules and synchronizing the processing rules to business nodes in real time; a business monitoring subsystem, which collects business indicators in real time through Kafka log streams; and a distributed data storage subsystem, which uses a distributed MySQL cluster to store meteorological data and caches it through Redis. This invention solves the problems of complex operation and maintenance, data backlog, poor scalability, and low reliability of traditional meteorological decoding systems by dynamically configuring business rules, distributed meteorological data decoding, distributed storage architecture, real-time monitoring and alarm mechanism, and fault tolerance function.

A computer-implemented method for model building with explainability is provided. The method includes receiving, by a hardware processor, a first metric and a second metric of minimum model performance. The first metric relates to data modeling quality and the second metric relates to model to business rule correlations. The method further includes performing, by the hardware processor, auto Artificial Intelligence model generation responsive to training data and a combination of the first and the second metrics of minimum model performance to obtain a model that is trained and meets model prediction accuracy and model prediction explainability requirements represented by the combination of the first and the second metrics of minimum model performance.

This invention belongs to the field of artificial intelligence technology and discloses a resource allocation method, apparatus, device, and storage medium. The allocation method includes: invoking a target business rule set and a target machine learning model that match the description information; generating a first initial allocation scheme based on rules and a second initial allocation scheme based on the model for the items to be allocated based on the target business rule set and the target machine learning model; generating a root cause diagnosis report when the difference between the first initial allocation scheme and the second initial allocation scheme exceeds a preset threshold; constructing a rule parameter optimization space based on the root cause diagnosis report; and searching for target rule parameters within the rule parameter optimization space that give the preset objective function an optimal solution, generating a final allocation scheme for the items to be allocated corresponding to the rule parameter optimization suggestions. This invention can be applied to business management systems in fintech, healthcare, and other fields, solving the technical problem of inaccurate resource reallocation.

The application relates to the technical field of nuclear power plant operation management and safety control, in particular to a nuclear power plant disturbance-free equipment determination method and system. The method comprises the following steps: acquiring feature data of a target equipment, constructing an input feature vector, inputting the input feature vector into a pre-trained disturbance-free equipment identification model, and outputting a prediction probability of the disturbance-free equipment; a rule function based on equipment business rules is constructed to correct the preset probability; the business rules comprise a master-slave relationship, a power supply subordination relationship or a strong position correlation relationship; the corrected prediction probability is input into a preset determination function to obtain a corrected prediction value; and the corrected prediction value is compared with a preset determination threshold to obtain a disturbance-free equipment set. The application performs multi-label prediction on the disturbance-free equipment based on the LightGBM algorithm, and introduces business rules to constrain and correct the model results, thereby improving the disturbance-free equipment identification accuracy, reducing the risk of missing identification of key disturbance-free equipment, and enhancing the nuclear power operation safety.

The application discloses a kind of table area electric heating load identification method and system, belong to power grid data analysis and intelligent identification technical field.The method includes: obtaining the historical load of to-be-identified table area, time and multi-dimensional time series data such as meteorology by data acquisition module;Utilize a deep learning model comprising time series feature extraction module and key feature weighting module to process data to generate preliminary classification results;Based on the business rules of the growth of heating season electricity consumption and the stability of non-heating season electricity consumption, the historical load is compared and verified across years;The preliminary classification result of model is combined with the verification result of rule, and whether table area is electric heating load is comprehensively judged.This application combines the pattern recognition ability of deep learning with the deterministic logic of business rules, realizes the high-precision, high-robustness automatic identification of electric heating load, and provides an effective technical means for power grid intelligent management.

The application discloses an AI-driven lightning bin replenishment strategy dynamic adjustment method, relates to the technical field of warehouse logistics artificial intelligence, and comprises the following steps: collecting multi-source heterogeneous data of a physical supply chain network and constructing a digital twin knowledge graph; extracting a dynamic attribute sequence from the digital twin knowledge graph, performing mode recognition based on a pre-defined business rule library and abnormality detection logic, obtaining a potential risk event, and injecting the potential risk event into the digital twin knowledge graph as a disturbance source node; performing multi-round message transmission and state iteration on the digital twin knowledge graph with the injected disturbance source node by using a graph neural network, simulating a cascading diffusion process of the risk along business edges and logistics edges, and obtaining a risk propagation report. The application solves the fundamental defect of gradual failure due to the lack of dynamic evolution capability, and ensures the prediction accuracy and the reliability of the decision.

The application relates to the technical field of airport operation management, in particular to an airport business rule management and task arrangement method and system based on digital twinning, which comprises the following steps: a rule script uploaded by a user is received through a rule management module, and a rule node is generated based on rule script encapsulation; a visual editor in a task management module is used to construct a business process task comprising a target node and a node data flow based on the user's dragging and connecting operation on the target node; real-time data flow is obtained from an airport digital twinning system based on the business process task through a real-time execution engine, a calculation corresponding to the rule node of the business process task is performed, and the calculation result is pushed to a downstream system or a front end in real time. In this way, flexible management of business rules, visual arrangement and automatic execution of tasks can be realized, and when subsequent business changes occur, the development personnel need not be involved to quickly respond to the business changes, so that the real-time decision-making capability and operation and maintenance efficiency of the airport are improved.

This invention relates to the field of network security technology and discloses a method and system for intelligent early warning of performance overload of network security devices. The method includes acquiring operating status data and response latency data; performing time-domain segmented feature extraction processing on the operating status data to obtain dynamic load trend features; performing anomaly verification and physical resource association mapping processing based on the response latency data and the dynamic load trend features to obtain system performance bottlenecks; extracting original alarm signals based on the system performance bottlenecks, and combining them with an alarm type rule base to perform business rule mapping to generate a final sequence, thus generating a final overload early warning sequence. This method can accurately distinguish between instantaneous traffic fluctuations and actual overload, trace hardware bottlenecks across dimensions, effectively eliminate invalid interference noise, and improve early warning accuracy.

The application discloses a kind of intelligent structured processing method and system of rules and regulations document, belong to artificial intelligence and natural language processing technical field.Along with the problem that the semantic of long regulation document in prior art is split due to the input length limit of large language model, output is unreliable, the application fuses the paragraph type by small model and semantic feature recognition, corrects label in combination with business rules, and aggregates semantic complete text fragment according to regulation level logic;The segment is constructed as guide prompt input large language model to generate structured result along with type label, and JSON format and field integrity check are set, and when check fails, it is returned to small model result.The method guarantees the integrity of clause-level semantics, improves the accuracy of key field extraction, and ensures system robustness.It is suitable for enterprise compliance management, regulation knowledge base construction and other scenarios, to realize the reliable conversion of unstructured regulation document to unified structured data.

This invention discloses a method, apparatus, equipment, and medium for indicator drill-down analysis. The indicator drill-down analysis method includes the following steps: acquiring the indicator to be analyzed and the analysis target input by the user, and obtaining the initial drill-down path of the indicator to be analyzed based on a preset indicator knowledge graph; performing drill-down analysis based on the initial drill-down path to obtain initial analysis results; expanding the initial drill-down path based on the initial analysis results to obtain the target drill-down path and the node drill-down analysis results of the corresponding path expansion nodes; and generating target analysis results that meet the analysis target based on the target drill-down path and the node drill-down analysis results. This method, by dynamically expanding the drill-down path, realizes the dynamic generation and execution of the target analysis path of the indicator to be analyzed, adapts to changing business rules, significantly improves the fit between the analysis results and the business scenario, and enhances the depth, flexibility, and accuracy of indicator analysis.

This invention belongs to the field of power system control and operation, and relates to a workflow implementation method and system for handling power grid monitoring alarm information based on a large model. It includes: a data acquisition step, collecting alarm information and storing it in a structured manner; a business rule filtering step, filtering alarm information and identifying fault events using preset rules; a power grid equipment knowledge base retrieval step, matching the equipment information corresponding to the event with the pre-built knowledge base to retrieve equipment parameters; a message generation step, inputting the filtered alarm information and equipment parameters into the large model to generate fault descriptions and handling suggestions; a daily report generation step, classifying and aggregating alarms within a set time period, and combining historical daily reports with the large model to generate a comprehensive alarm daily report; a message push step, pushing the fault description, handling suggestions, and daily report to the dispatch terminal; and a query and display step, displaying and supporting status confirmation and query. This invention achieves intelligent handling and in-depth analysis of alarm information, improving power grid monitoring efficiency and decision support capabilities.

This invention provides a sky-ground network collaborative natural resource monitoring and supervision method and system, belonging to the field of information technology for natural resource monitoring and supervision. It can at least partially solve the problems of insufficient multi-source data collaboration, coarse interpretation results, rigid business rules, and low efficiency in cross-level and cross-departmental collaboration in existing natural resource monitoring. The method includes: constructing a sky-ground network collaborative sensing network to achieve multi-scale, multi-temporal monitoring and unified scheduling; intelligently interpreting multi-source data and outputting vectorized results; executing configurable monitoring and analysis rules on the interpretation results to generate early warning information; automatically generating standardized work orders from the early warning information and distributing, handling, and providing feedback at multiple levels (city, county, township) and across departments according to a preset process. This solution achieves full monitoring coverage, high-precision interpretation, and a closed-loop collaborative handling mechanism.

The application discloses a kind of dynamically configured service logic method, cloud platform, vehicle and storage medium, the method includes: receiving configuration information;According to the configuration information, scene decision tree is dynamically configured, configuration message is generated, and is issued to vehicle;Wherein, the scene decision tree is obtained by the service logic of the preset event library by sceneization.This application is dynamically configured to the scene decision tree set on cloud platform, configuration message is obtained, and is issued to vehicle to upgrade software system in vehicle, can quickly respond to demand change, without software developer to do repetitive tedious development work, so that non-technical personnel can also participate in editing maintenance system business rules, simultaneously without OTA upgrade iteration, can reduce the cost and risk of software system upgrade.

The present disclosure provides an advertisement search model construction method and device, electronic equipment and storage medium, relates to the technical field of computers, in particular to the fields of data processing, intelligent search, and can be used in application scenarios such as advertisement pushing. The specific implementation scheme is: constructing a business rule prefix tree according to the delivery rule of an advertisement database; generating rule-aware training data according to search logs; training a generative model using the rule-aware training data, so that the generative model learns to output a target advertisement identifier bound to a rule identifier; integrating the business rule prefix tree and the trained generative model to form an advertisement search model. This scheme generates an advertisement identifier by fusing business rule features through a model, significantly improves the relevance of recalled advertisements and user intent, reduces invalid exposure rate, and optimizes advertisement conversion link accuracy.

This invention discloses a script-based navigation-based IoT gateway configuration method, apparatus, device, and medium. The method includes: obtaining a navigation configuration file; dynamically generating a configuration interface based on the navigation configuration file, the configuration interface presenting a wizard-style configuration process according to page nodes and jump logic, during which IoT devices in the network are scanned for user selection; generating recommended data mapping relationships based on the protocol characteristics of the discovered IoT devices for user confirmation or adjustment; generating a rule editing interface based on declarative syntax to receive user-defined business rules; generating configuration data based on user operations and execution results on the configuration interface, and generating a gateway configuration file based on the configuration data; and deploying the gateway configuration file to the IoT gateway. This invention achieves script-based dynamic customization of the configuration process, allowing flexible adjustments to the configuration wizard without modifying the source code, lowering the configuration threshold and improving configuration efficiency.

This invention provides a material re-inspection management method and system based on blockchain-based evidence storage and physical identification, belonging to the technical field of bulk material sample and surplus material management. By solidifying a rigid on-chain re-inspection process, the flexible manual process is transformed into a rigid on-chain program, ensuring the authenticity and transparency of the process. By synchronizing the digital lineage association and status of samples and surplus materials, the core pain point of broken traceability relationships after physical separation is overcome, achieving refined tracking. Through a rule-driven compliance handling method based on smart contracts, the code-based and automated execution of business rules is realized, completing the management closed loop.