463 results about "Business data processing" patented technology

The invention provides a service data voice processing method and system based on artificial intelligence, and relates to the field. The service data voice processing method based on artificial intelligence comprises multi-mode voice preprocessing, domain enhancement voice recognition, knowledge graph driven semantic analysis, a dynamic dialogue management mechanism and a closed-loop feedback optimization system. According to the method, high-precision recognition, semantic understanding and structured processing of the service voice data are realized by fusing the domain knowledge graph, the dynamic model optimization and the context sensing technology, and the service data processing efficiency and accuracy are improved; secondly, the system comprises a voice acquisition and preprocessing module, an AI voice processing module, a business data processing module, a model optimization module and a data interface module, the efficiency and accuracy of business data voice processing can be remarkably improved, and the system is suitable for various professional scenes such as finance, customer service and medical treatment.

The invention discloses a vehicle rental management system and device based on the Internet and a storage medium, and relates to the technical field of vehicle rental, and the system comprises a client management module which is used for collecting client information, and the client information comprises the personal information of a client and a vehicle rental demand; the vehicle management module is used for synchronizing the vehicle rental state to the rental management module and monitoring the vehicle use condition during the rental period; the lease management module is used for generating a lease scheme according to the vehicle lease demand and the vehicle use condition; and the data sharing interface module performs data exchange with a third-party system through an API interface, synchronizes business data generated in each link in the vehicle rental business process to the third-party system in real time according to the vehicle rental business process, and receives a business data processing result returned by the third-party system. According to the invention, the third-party system is integrated, so that the online vehicle rental business process and the real-time information intercommunication are realized, and the business cooperation efficiency is improved.

The invention relates to the field of enterprise business management, in particular to an AI-based enterprise business data processing system and method, and the method comprises the steps: 1, obtaining source system data, and storing the obtained data in one or more target systems; step 2, constructing a data synchronization strategy, and monitoring and managing data synchronization between the target system databases based on the data synchronization strategy: generating the data synchronization strategy based on the data synchronization cost; after the importance of the data and the data synchronization task is quantified, the data and the data synchronization task are combined with the data synchronization cost, and a data synchronization strategy is optimized; an adjustment rule is added in the optimized data synchronization strategy, and the importance of data or tasks is dynamically adjusted; and step 3, sending the data of the one or more target systems to the cloud platform for storage.

The invention provides a data processing method based on request interception, which comprises the following steps of: intercepting a calling request for marking a service method through a request interception mechanism, preposing a decision point of service logic, and selecting whether the service method is executed or not according to a request context. According to the method and the device, the business rules are stored in the configuration center, external rule configuration is performed, the business rule expressions are pre-stored in the configuration center, dynamic acquisition is performed based on the rule identifiers, decoupling of the business rules and the codes is realized, the business rules can be configured independent of the codes, and flexible business processing can be realized only by modifying the expressions of the corresponding rules in the configuration center. The problems of code expansion and difficult maintenance caused by business rule change in a multi-channel environment are effectively solved, so that the flexibility and maintainability of a business data processing system are improved. The method can be applied to a business processing system in the financial field or the medical field, so that the flexibility of the business processing system in the financial field or the medical field is improved.

The invention discloses an intelligent processing method for automatic settlement of review labor reward of a review expert, and belongs to the technical field of business data processing, and the method comprises the steps: obtaining text revision trajectory data and cooperative interaction data of the review expert, and generating a review behavior feature vector; performing recessive workload analysis on the review behavior feature vector to generate a quality weight factor; obtaining project environment parameters, and calculating to obtain a reward amount according to the project environment parameters, the quality weight factor and a preset settlement coefficient; performing exception verification on the reward amount, if the verification is passed, executing payment operation, and otherwise, triggering a manual rechecking process; and updating the settlement coefficient according to the feedback data after payment. According to the method, the reward is dynamically calculated by quantitatively reviewing the behavior characteristics and fusing the environmental parameters, and an exception verification and closed-loop optimization mechanism is established, so that fair and efficient full-process automatic settlement can be realized.

The invention relates to a business data processing method and system, equipment and a medium. The method comprises the following steps: preprocessing multi-source heterogeneous cross-domain economic data to generate a standardized data stream; semantic drift in the standardized data flow is detected in real time, and a detection result is generated; semantic alignment judgment is carried out based on the detection result, and a dynamic alignment signal is generated; performing incremental training of a mapping model by using the dynamic alignment signal to generate an updated cross-domain mapping model; and finally, performing mapping conversion on the data stream based on the updating model, and outputting service data with unified semantics. By adopting the method, the semantic change in the economic data can be responded in real time, the problems of semantic drift detection lag, long model updating period and high maintenance cost in the traditional technology are effectively solved, and the accuracy and timeliness of cross-domain economic data processing are remarkably improved.

The embodiment of the invention discloses a product business data processing method and device for an ERP business scene and a medium, and relates to the technical field of ERP, and the method comprises the steps: obtaining historical sales data, supply chain data and external environment data of a target product in an ERP system under the triggering of a business index prediction request, and obtaining a business index prediction result of the target product based on the supply chain data; determining a plurality of dynamic time scales corresponding to the target product to determine a multi-dimensional feature set corresponding to each dynamic time scale; determining a business index linear predicted value and a nonlinear residual sequence through an ARIMA model and each multi-dimensional feature set; according to the external environment data, performing decomposition prediction on the nonlinear residual error sequence to determine a reconstructed residual error sequence, and determining current service index prediction data corresponding to each dynamic time scale based on the service index linear prediction value and the reconstructed residual error sequence; and performing multi-scale fusion on the business index prediction data corresponding to each dynamic time scale, and determining target business index prediction data of the target product.

The embodiment of the invention provides a business data processing method and device, electronic equipment and a storage medium, and relates to the technical field of data processing. The method comprises the following steps: generating a query semantic vector according to a data query problem; performing table data query operation in the business knowledge base according to the query semantic vector to obtain data table information; generating an initial cue word according to the data table information; obtaining a to-be-executed structured query statement according to the initial cue word, the data query problem, the business database and the fine-tuned proprietary large model; inputting the to-be-executed structured query statement into a preset executor, and when the execution result of the preset executor executing the to-be-executed structured query statement is successful, executing query operation from the business database to obtain preliminary result data; and performing presentation processing according to the preliminary result data to obtain to-be-presented data. Conversion from a natural language data query problem to a structured data query problem is realized, and the technical effect of enhancing the accuracy of a query result is achieved.

The invention discloses a business data processing method and device, a storage medium and electronic equipment. The method comprises the following steps: executing a target interaction operation in response to a first account, skipping to a first application, and acquiring a first image currently displayed by the first application and a business process template associated with the first application, the first image being used for indicating that the first account is acquiring business data associated with a target business, and the business process template being associated with the first application; the business process template is used for indicating an image feature corresponding to a process node of the target business; whether a target template exists in the business process template or not and whether the first application runs in a system foreground or not are inquired based on the first image, and image features of the target template and image features of the first image meet preset matching conditions; and under the condition that the target template exists and the first application always runs in the system foreground, executing a character recognition operation on the first image, and determining business data. The technical problem that the processing accuracy of the business data is relatively low is solved.

The invention discloses a method, a system and a device for updating data in a database and a program product. The method comprises the following steps: controlling a data synchronization module to generate a data acquisition request; in the first data processing area, in response to the data acquisition request, acquiring data to be supplemented from a first database corresponding to the first data processing area, and transmitting the data to be supplemented to a data synchronization module, and physical isolation does not exist between the first data processing area and the host system; the data synchronization module is controlled to synchronize the data to be supplemented into a second data processing area, and physical isolation exists between the second data processing area and the host system; and in the second data processing area, according to the to-be-supplemented data, updating the data in the second database corresponding to the second data processing area. The technical problem of low business data processing efficiency is solved.

The invention discloses an engineering building construction quality analysis system and method based on data processing, and belongs to the technical field of commercial data processing and intelligent decision, and the system comprises a causal relationship graph construction module which is used for fusing multi-source monitoring data to construct a causal relationship graph; the risk profile construction module is used for performing reverse deduction and forward simulation and constructing a prospective quality risk profile; the multi-target collaborative optimization module is used for solving a Pareto optimal equilibrium solution set; the quality pre-control instruction generation module is used for instantiating a dynamic quality pre-control instruction; the efficiency evaluation and attribution correction module is used for updating the causal relationship graph; and the evolution auditing and causal knowledge distillation module is used for auditing historical updating of the atlas and distilling a core causal rule set. According to the method, risk deduction and simulation are carried out by constructing the dynamic causal relationship graph, and multi-objective optimization and closed-loop feedback correction are combined, so that prospective identification and collaborative intelligent pre-control of the project quality risk can be realized.

The invention relates to the technical field of engineering project management, and discloses an engineering project supply chain collaborative management system, which comprises a unified data interface module used for acquiring multi-source business data from heterogeneous information systems of an engineering project general package party, a sub-package party, a material supplier and a logistics service provider, processing the multi-source business data into a standardized business data model; and a business process management module. By adopting the technical scheme that a unified data interface module and a workflow engine cooperatively work, the technical effects of connecting information systems of all participants of a supply chain and realizing automatic synchronization of purchasing, inventory and construction progress data and linkage of a business process are achieved; compared with the technical scheme that each party adopts an incompatible information system and depends on manual information transmission in the prior art, the defect that the accuracy of a project plan is damaged due to difficulty in collaborative operation caused by data obstruction is overcome.

The invention relates to the technical field of visual lane modeling, and discloses a business data processing method and system based on visual lane modeling, and a multi-task prediction model based on multi-source historical business chain data training graph neural network and Transform fusion. A plurality of groups of lane layout and event configuration schemes are generated in combination with user real-time operation captured by a design interface, an optimal scheme is screened through simulation evaluation and then is visually displayed, finally, visual lane modeling is executed according to user feedback, and through automatic data processing, high-precision model prediction, real-time interaction optimization and visual modeling, the optimal lane layout and event configuration scheme is obtained. According to the method, the service chain design efficiency and quality are improved, meanwhile, artificial experience deviation is avoided through model prediction based on historical data, the comprehensive requirements of complex equipment development for real-time performance, reliability and resource efficiency are met, and efficient technical support is provided for landing of model-based system engineering in the field of complex equipment.

The invention provides a business data integrity encryption method and device, equipment and a storage medium. The method comprises the steps that database fields participating in integrity encryption are marked; the business processing layer processes data input by a user or generated by a system, carries out business data processing, carries out interception operation before SQL statement execution by utilizing a MyBatis interceptor, checks fields contained in SQL statements, splices all marked field data according to a predefined field splicing strategy, and carries out data processing on the spliced field data; performing encryption processing on the spliced field data through an encryption algorithm, and assigning a generated hash value to a corresponding field; and the database executes the modified SQL statement to complete data insertion or updating operation so as to ensure that the data stored in the database is completely encrypted data. According to the application, non-intrusive encryption and verification logic are realized through the MyBatis interceptor, and the security and maintainability of the system are improved.

The invention discloses a power grid business data feature extraction method, which belongs to the technical field of power grids, and comprises the following steps: periodically collecting power grid business data; performing primary processing and feature extraction on the power grid service data to obtain basic feature data; performing feature re-extraction and analysis on the basic feature data to obtain advanced feature data; performing anomaly detection on the basic feature data and the advanced feature data, and judging whether an anomaly detection result is abnormal or not; and when the anomaly detection result is abnormal, triggering an alarm mechanism, and adjusting a feature extraction strategy. According to the power grid business data feature extraction method, multi-level feature extraction and real-time anomaly detection are adopted, and efficient, accurate and real-time power grid business data processing can be achieved.

The invention relates to a business data management method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps of obtaining business data of a product, and performing feature extraction to obtain an extracted business feature vector; the business data comprises the order quantity, the serial number of the minimum stock unit of the product, the quantity of the minimum stock unit and the storage timestamp; clustering different products based on the service feature vectors to obtain a preliminary clustering result; using the product orders and the minimum inventory units as nodes to construct a graph neural network, and further clustering and combining the preliminary clustering results through the trained graph neural network to obtain a final clustering result; and according to the final clustering result, calculating a corresponding shortest sorting path. By adopting the method, the utilization rate of the business data can be improved, so that the cost is reduced, and the business data processing efficiency is improved.

The invention provides a method for dynamically dividing data into buckets. The bucket redistribution operation mode is dynamically determined by obtaining the bucket distribution heat parameter of the service data and the load parameter of the computing node in real time. And based on joint judgment of the popularity and the load, triggering a bucket splitting or merging operation, generating a target bucket scheme and storing an incremental snapshot, thereby ensuring that the affiliation relationship of the business data in the bucket adjustment process is clear and traceable. The incremental snapshot provides a core basis for lossless recovery of a subsequent calculation state by recording bucket metadata, calculating offset and intermediate result data. Furthermore, by predicting an expected load parameter of a computing node and combining a target bucket distribution scheme, the bucket distribution is dynamically distributed to a load matching node, and the problem of resource distribution stiffness of static bucket distribution is solved. The computing node recovers the business data processing flow based on the incremental snapshot, so that repeated calculation or loss of data caused by bucket adjustment is avoided, and the real-time data processing efficiency, the resource utilization rate and the business continuity are remarkably improved.

The invention provides an optimization method for expression calculation during data mapping rule field mapping, and belongs to the technical field of business data processing. The method comprises the following steps: based on a plurality of expressions on a mapping unit, extracting a source table and field information required by expression calculation; setting context data required by expression calculation based on the source table, the field information and the source data; on the basis of the context data, expression calculation is conducted in a multi-thread mode, a calculation result is generated, the context of source data in each thread is the same, and calculation of all expressions of one mapping unit is executed in one thread; and combining calculation results, and generating a target data set. The performance loss and initialization time of expression calculation are effectively reduced, and the execution efficiency and speed of the data mapping rule in a large-scale data processing scene are improved.

The utility model relates to the technical field of intelligent power distribution, and especially relates to an Internet of Things feeder terminal device. The Internet of Things feeder terminal equipment adopts a dual-system core board, adopts a dual-core heterogeneous core scheme of a real-time core and a non-real-time core according to the real-time and non-real-time requirements of medium-voltage distribution network service data processing, supports multi-service identification processing, and is widely applied to Internet of Things transformation and upgrading of various medium-voltage distribution equipment. Through a built-in 5G communication module, point-to-point communication between devices is realized, millisecond-level data transmission is supported, low delay and reliability of data transmission are ensured, and a scheme of in-situ rapid fault isolation such as differential protection is realized. The device also supports an MQTT Internet of Things protocol, can realize edge calculation, has the characteristics of hardware platformization, software APP, software development interface standardization, edge calculation and the like, and can be accessed to sensing layer equipment of various communication types. And the device supports plug and play, has a self-description capability, and realizes software and hardware decoupling.

The invention discloses a cross-system service data processing method, device and equipment, a medium and a product. The cross-system business data processing method comprises the following steps: establishing a dynamic field mapping relationship between an integration layer and a plurality of target business systems; extracting capital construction business data from the target business system through the integration layer according to the dynamic field mapping relationship, and performing standardization processing to obtain standard business data; aiming at each stage of the capital construction project, constructing corresponding index data to obtain an index system; on the basis of an index system, index penetration query is carried out on standard business data, and a linkage management and control mechanism of an index abnormal item and an infrastructure project three-dimensional model is established; on the basis of the multiple access roles, corresponding visual billboards are distributed, and the visual billboards support index display; and based on a preset data quality rule base, performing quality evaluation on the standard business data, and identifying data abnormal items. According to the technical scheme provided by the embodiment of the invention, integrated management and control of cross-system business data are realized.

The invention relates to the technical field of business data processing, and discloses an industrial multi-project multi-level index calculation method, system and device and a storage medium, and the method comprises the steps: collecting multi-dimensional data from different industrial projects and levels, and carrying out the preprocessing; establishing an analysis model by using the preprocessed data, and analyzing the dependency relationship among the data indexes; based on the analyzed dependency relationship, forming an initial hierarchical structure, and automatically adjusting the hierarchical structure according to data and business requirements; and optimizing calculation path selection and resource allocation. The hierarchical structure is formed and automatically adjusted by dynamically analyzing the dependency relationship between the data, so that the system can flexibly meet complex industrial data processing requirements. The calculation path selection and the resource allocation are optimized, and the data processing efficiency and the decision accuracy are improved. And the intelligence and practicability of industrial multi-project multi-level index calculation are remarkably improved.

The invention discloses an air ticket order optimization method and system combined with big data, and relates to the technical field of air ticket business data processing. The air ticket order optimization method comprises the steps of multi-source heterogeneous data acquisition, federal feature fusion processing, dynamic pricing decision making, user implicit demand mining and real-time risk early warning and resource allocation, and has the advantages that the system supports real-time integration of aviation operation data, external environment data, user behavior data and market dynamic data; the limitation that a traditional system only depends on data in a single field is broken through, scattered multi-source data is converted into global features reflecting market trends, user demands and potential risks through a federal feature fusion technology, multiple influence factors such as flight transport capacity, user preferences and external events can be considered in the decision making process, and the decision making efficiency is improved. And the decision-making capability of the system in a complex scene is effectively enhanced.

The invention relates to an informatization multi-service data integration method, system and device and a medium, and belongs to the technical field of service data processing. The integration method comprises the steps that a target data source is collected and initialized; structured data and semi-structured data are regularly and automatically extracted from the target data source to a source-attached data source through an ETL (Extract-Transform-Load) engine; performing digital semantic analysis on the unstructured data in the target data source, and performing partial structured processing according to a digital semantic analysis result to obtain partial structured data; taking structured data, semi-structured data and partial structured data in the source data source as a to-be-integrated data source; and performing data integration on the data in the to-be-integrated data source, synchronizing the integrated data to the short-term data center in real time, performing data aggregation, obtaining the aggregated data, and storing the aggregated data to the comprehensive data center. According to the method, data integration is effectively realized in an enterprise multi-source heterogeneous data environment, and the data management and decision-making requirements of an enterprise can be better supported.

The invention belongs to the technical field of artificial intelligence, and provides a service processing method and system based on multi-agent collaborative group chat in order to solve the problem of poor accuracy of a service data processing result. The business processing method based on multi-agent collaborative group chat comprises the steps of constructing a business data processing chat group; receiving a current user message of a human user, calling an analysis manager agent to perform intention analysis on the current user message, and judging whether an intention analysis result belongs to a current service data processing task or not; if yes, an analysis manager agent is called to distribute a user message to a corresponding service expert agent to reply and judge whether manual intervention is needed or not until the current service data processing task is completed; otherwise, calling an analysis manager agent to judge whether the current user message is an analysis demand, and if yes, responding to the analysis demand until the analysis demand is completed. Manual correction and intervention can be carried out at any time in a chat group form, and the accuracy of a service data processing result is improved.

The invention belongs to the technical field of program control systems, and particularly relates to a Qt-based EtherCAT master station system and a multi-task scheduling method. The system comprises a man-machine interaction module, a task scheduling management module, an EtherCAT master station protocol stack function module, an XML slave station configuration file analysis module, a network port communication module and a serial port communication module. The man-machine interaction module comprises service real-time display and control, EtherCAT communication data online debugging, service basic configuration and modular debugging and system authentication; the task scheduling management module comprises a system working state management module, a complex business data processing module and a task scheduling module; the EtherCAT master station protocol stack function module comprises real-time data processing of a controlled object, business control logic management of a controlled slave station, an EtherCAT master station initialization process and business processing process interface implementation of the controlled object. The development efficiency and the system performance of the EtherCAT master station system are remarkably improved, and the requirements of a modern industrial control system for real-time performance, stability and user experience are met.

The invention discloses an efficient data processing method, device and product based on multiple tenants, and relates to the technical field of business data processing. The data processing method comprises the following steps: receiving a business data processing request initiated by a target tenant; verifying whether the target tenant is a valid tenant; if the target tenant is a valid tenant, determining a database allocation strategy corresponding to the target tenant based on a pre-configured database allocation strategy; if the database allocation strategy corresponding to the target tenant is an independent database allocation strategy, obtaining an exclusive connection character string of the target tenant, and determining an exclusive database corresponding to the target tenant based on the exclusive connection character string of the target tenant, and executing a business data processing operation corresponding to the business data processing request on first business data in an exclusive database corresponding to the target tenant. The problem of database lock competition can be avoided, the system throughput is improved, and the response delay is reduced.

The invention discloses a reinforcement learning insurance business data processing system, which combines objective I oT real-time data representing a physical environment and an equipment state and employee behavior compliance data reflecting human factors and a process adherence condition, and innovatively uses I oT data to carry out cross validation on employee behavior data so as to ensure data quality. And then, the verified high-quality multi-dimensional data stream is input into a reinforcement learning model, the model dynamically optimizes a decision strategy through continuous learning environment feedback (such as enterprise operation state and risk change), and finally, a targeted and intelligent enterprise insurance service processing result (such as dynamic pricing, risk early warning and fraud identification) is output. Therefore, a complete intelligent closed loop from data acquisition, verification and learning to decision making is formed.

The invention relates to a business data processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps of obtaining first business data, target data belonging to a target dimension in the first business data being range data, and the range data being data comprising at least two values; determining a data coding system based on a value range of target data in the first business data; according to the data coding system, coding target data in the first service data to obtain a system coding result, the system coding result comprising the data coding system and system coding range information corresponding to the target data; and performing data compression on the first service data based on the system coding result to obtain first compressed service data corresponding to the first service data. By adopting the method, the business data processing efficiency can be improved.

The present application provides a business data processing method, device, electronic device and medium, the method comprising: obtaining target business data from multiple different data sources; sending the target business data to multiple types of data processing servers; different types of data processing servers process the target business data based on configured data processing rules, respectively determine the target business feature data that matches the types of the different types of AI model servers, and send them to AI model servers of matching types; different types of AI model servers process the received business feature data based on pre-configured and trained business volume prediction models, and determine different types of business volume prediction results; and fuse the different types of business volume prediction results to determine the target business volume prediction result, thereby improving the data processing speed and the real-time level and prediction accuracy of business volume prediction.

The invention discloses a business data processing method and system based on multiple channels, and the method comprises the steps: obtaining the basic information of a to-be-sold commodity and a preset advertisement putting amount, calculating the average re-purchase period of the commodity through analyzing the historical business data of each channel, comparing the remaining re-purchase time of a user with the average re-purchase period, and determining a first intention user. If the number of the first intention users meets the advertisement putting demand, allocating the advertisement putting amount and screening the advertisement putting users based on the remaining re-purchase time and a preset advertisement putting preference prediction algorithm; otherwise, the second intention users who have purchased the commodities recently are found out by analyzing the commodity set with high relevance, and the final advertisement putting object is determined by combining the conditions of the two types of intention users. According to the invention, by analyzing the multi-channel business data and the user re-purchase cycle, the intentional user is accurately positioned, the advertisement putting is optimized, and the advertisement conversion rate and the resource utilization rate are effectively improved.