130 results about "Business environment" patented technology

The invention relates to the technical field of data analysis, in particular to an operation decision intelligent analysis method and system based on cross-domain data fusion. The method comprises the following steps: firstly, based on an enterprise multi-domain ontology knowledge base, performing entity identification and relation mapping on heterogeneous data from different business systems through a semantic mapping-based multi-source heterogeneous data dynamic fusion algorithm, and establishing a unified data model; then, a causal reasoning and deep learning fused hybrid intelligent decision engine is adopted to analyze and process the model; then, a multi-level causal relationship network among business variables is constructed through a causal relationship discovery algorithm by utilizing an analysis result of the hybrid intelligent decision engine, and an adaptive business scene analysis model based on reinforcement learning is used to dynamically adjust an analysis strategy according to business environment changes; generating a Pareto optimal decision scheme set through a multi-objective optimization algorithm, and outputting operation decision suggestions; according to the invention, the comprehensiveness and accuracy of intelligent analysis of enterprise operation decisions are improved.

The invention discloses a storage resource management method and system and a storage medium, and relates to the technical field of storage resource management, and the method comprises the steps: calculating the access popularity and popularity threshold of data according to a historical log file, and carrying out the popularity layering of the data in the historical log file according to the two; the data distribution mapping table is generated based on the historical log file and the access popularity, and finally multiple storage resources are allocated based on the layered data and the data distribution mapping table, so that the problems that application scenes of related technologies are limited, and the performance of a storage system is difficult to flexibly deal with complex and changeable business environments are solved; the technical problem that smooth expansion and rapid iteration of a storage system cannot be achieved is solved, and the technical effects of dynamic allocation, efficient utilization, flexible configuration and safety protection of storage resources and capability of leisurely coping with various complex application scenes are achieved.

The invention discloses a code generation method and device based on model low-code application and a medium, which are used for solving the problems that the expansibility and the adaptability of a system are sacrificed due to platform limitation in the prior art, and the traditional coding is difficult to meet the rapid trial and error and continuous iteration efficiency required by a modern commercial environment. The method comprises the following steps: constructing a corresponding application model through a menu, a webpage and a form based on a low-code platform, compressing the application model, and uploading the compressed application model to a remote object storage service; performing version verification on a target model determined in the application model, analyzing the target model passing the verification, and generating front and rear end codes corresponding to the target model; and pushing the front-end code and the rear-end code to a GitLab warehouse, and configuring an automatic process corresponding to the rear-end code based on an assembly line in the GitLab warehouse to realize automatic operation of code generation. Through the scheme, the development efficiency is greatly improved, the manual coding risk is reduced, and the user requirements are met with low cost.

The invention discloses a white list state synchronous processing method and system combined with database transaction control, and relates to the technical field of database transaction control and data synchronous processing. The method comprises the following steps: recording a white list state change event based on a pre-writing mechanism of a database transaction log; change events in a transaction log are classified and aggregated according to a white list and then are asynchronously written into a specified buffer area, when a transaction is submitted, the sequence of data in the buffer area is controlled through a lightweight lock mechanism to be refreshed to a physical disk, and the priority of a disk IO queue is dynamically adjusted according to the transaction isolation level to reduce concurrent conflicts; according to the white list state synchronization processing method and system combined with database transaction control, the transaction concurrent processing performance and the database response efficiency are remarkably improved, and the expansion capability and stability of the white list synchronization system in a complex business environment are also improved.

The invention discloses a business process control method and system based on a decision engine, and relates to the technical field of business process control. The method comprises the following steps: collecting environmental change data in a business process in real time, classifying and filtering the data, and dividing the data into a significant change group and a tiny fluctuation group to obtain an environmental change core set; strategy matching analysis is carried out on the significant change group, and an adaptive decision adjustment scheme set is determined; then, the execution efficiency and stability of all the schemes are evaluated through historical execution records, comprehensive sorting is carried out, and candidate decision combinations are determined; and finally, evaluating the applicability of the candidate scheme in combination with environmental characteristics. According to the method, quick response to environment change is realized, through historical data analysis and multi-dimensional evaluation, the decision making process is optimized, the decision making accuracy and execution efficiency are improved, the applicability of a complex and changeable business environment is improved, and dynamic optimization and continuous improvement of decision making are realized.

The invention discloses an agent-free real-time backup method for a virtual machine of a privatized cloud platform, which comprises the following steps of: starting a backup service of a transmission unit, loading an eBPF program and initializing a configuration file; creating and initializing a shared memory; an eBPF program is loaded on a host machine, and the eBPF program is attached to a related function for processing a virtio-blk write IO request; the eBPF program intercepts a write IO (input / output) of virtio-blk equipment in the host machine, and data parameters are analyzed; the eBPF program encapsulates the write IO request and adds the encapsulated write IO request data structure into a shared memory; the backup service of the transmission unit reads the data from the shared memory and transmits the data to the storage unit; according to the method, complex snapshot operation and related resource consumption work such as data comparison and merging do not need to be carried out, the influence of the backup process on the performance of a service environment is small, the dependence on a virtualization platform is reduced, the method has higher universality and portability, and the limitation of a traditional backup method is effectively solved.

The present invention relates to the field of store location recommendation, and discloses a store location recommendation method integrating multi-dimensional features, which includes the following steps: S10. Collect multi-dimensional data of the area where the candidate store location is located, and the multi-dimensional data includes: pedestrian flow, number of competing products, price, industry market size growth rate, regional planning trend, and consumer population change trend; S20. Preprocess the multi-dimensional data, including data cleaning and normalization processing; S30. Input the preprocessed multi-dimensional data into the store location recommendation model to obtain the recommendation value of each candidate store location; S40. After arranging the recommendation values of each candidate store location in descending order, obtain the store location recommendation sequence. The multi-dimensional data of the present invention is used for store location recommendation and fully considers various key factors affecting store operation, more comprehensively depicts the business environment of the candidate area, and thus can provide more accurate store location recommendations for stores, effectively improving the accuracy of location selection.

The invention discloses a high-interaction deception defense and attack tracing method based on an RASP technology, and the method specifically comprises the following steps: S1, RASP implantation and bait deployment, S2, attack detection and simulation triggering, S3, attack session redirection and high-interaction deception, S4, attack behavior monitoring and tracing data collection, and S5, tracing analysis and threat disposal. The invention relates to the technical field of network and information security. According to the high-interaction deception defense and attack tracing method based on the RASP technology, a deception mechanism is embedded into a real application / system in operation, and high fusion of a real business environment and a false trapping environment is achieved. Different from a traditional'main-auxiliary separation 'mode that a honeypot is placed in an independent network or a host, the method has the advantage that the application can be changed to generate a'trap' during running through the RASP. The seamless embedded spoofing makes attackers difficult to distinguish true and false: the attackers attack a part of a production system initially, and then are introduced into a parallel simulation space unconsciously.

The invention provides an automatic planning integrated service system based on artificial intelligence. The automatic planning integrated service system based on artificial intelligence comprises a multi-source heterogeneous data access and processing module used for preprocessing multi-source heterogeneous data from a sensor, a historical business log and a third-party API in real time; the data unified modeling and storage module is used for carrying out semantic modeling storage on the multi-source heterogeneous data through a knowledge representation model; and the intelligent planning and scheduling module is used for reasoning and optimizing the timeliness, the cost and the resource utilization rate. According to the automatic planning integrated service system based on artificial intelligence, a decision strategy can be continuously refined, and it is ensured that an optimal or near-optimal scheduling scheme is always provided in a complex and changeable business environment, so that the overall operation efficiency and the resource utilization level are remarkably improved.

The invention provides a business resource optimization management method and system based on computing power demand prediction, and the method comprises the steps: collecting multi-source heterogeneous data in real time, so as to construct and continuously update a topological graph which represents the dynamic association relationship among a business entity, a logic service entity and a physical resource entity; a time sequence state of a topological graph is input into a prediction model fusing a graph structure and continuous time modeling, multi-dimensional evolution calculation of a node state is carried out by the prediction model, a dynamic resource value signal is generated by a central scheduler under a hierarchical decision framework, a plurality of service unit intelligent agents are guided to carry out distributed collaborative decision, and a multi-dimensional resource value signal is generated by the central scheduler. Iteratively generating an optimal resource allocation scheme; and before the optimal resource allocation scheme is executed, potential risk assessment and credible automatic execution are carried out. Therefore, in a complex dynamic commercial environment, the computing power resource is converted from global perception, accurate prediction and intelligent optimization to risk-controllable closed-loop management and adaptive configuration.

Robust systems and methods are disclosed for fake account detection on digital platforms, integrating provenance analysis to scrutinize data origins, ownership, and history, thereby unveiling potential sources of fraudulent activities. They leverage dynamic feature generation, using advanced algorithms to assess user behaviors and interactions, ensuring the model stays attuned to the evolving landscape of cyber threats. Incorporating Quantum-assisted optimization, the method employs Quantum algorithms to expedite feature selection, enhancing detection efficiency. Quantum simulation further refines this process, creating sophisticated verification patterns and analytical techniques to distinguish genuine from fake accounts with higher accuracy. A comprehensive analysis amalgamates provenance data, telemetry, and dynamic features, forming a holistic detection approach. This system optimizes features through Quantum simulation, tailoring them to specific business environments, and deploys them via AI-ML DevOps, streamlining orchestration across various operational settings.

The invention provides a non-perceptual data dynamic migration method which comprises the following steps: acquiring a difference between a source database and a target database, and making a data lossless migration plan; comparing the data difference between the source database and the target database, judging the data volume needing to be synchronized each time, and predicting the required network bandwidth resources; estimating transmission time sequences and transmission paths of different data blocks by using a Kalman filtering algorithm according to importance and priority of an application system and data; continuously monitoring data synchronization quality and application system performance indexes in a data migration task execution process, and judging a smooth transition effect; after core service data migration is finished, paused non-core services are recovered step by step until migration and synchronization of all service data of the standby data center are finished; a gray release mode of gradually expanding the weight is adopted, the service is smoothly transited to a data center, and a one-key automatic full-service environment rollback scheme is established to prevent abnormity.

The invention discloses a distributed service credibility authentication method and system oriented to a cloud computing environment, and relates to the technical field related to cloud computing credibility authentication, and the method comprises the steps: receiving an authentication request of a distributed service; establishing an authentication path by using the service state evaluation result; obtaining a unique verification voucher and calling an authentication data set of the user; sending the authentication reference voucher to a plurality of authentication nodes; calling a smart contract to carry out authentication analysis on the authentication data sets of the plurality of authentication nodes; using a distributed account book to record authentication process data and a node authentication result, and generating an authentication attitude quantity; and if the authentication attitude quantity is an authentication passing result, granting the access authority. The technical problems that in the prior art, a dynamic service environment is difficult to adapt, cross-system authentication interoperability is poor, and the authentication process lacks effective recording and tracing, so that authentication efficiency, accuracy, safety and credibility are poor are solved, and the technical effect of improving the accuracy, efficiency and safety of distributed service credible authentication is achieved.

The embodiment of the invention provides a method, device and equipment for training a workflow to create a model, a storage medium and a program product. The method comprises the steps of obtaining a creation request for creating a workflow for a data object; acquiring data of a workflow corresponding to the creation request, wherein the workflow is created based on the creation request and the information of the data object; based on the data of the workflow, determining first sample data related to a workflow framework of the workflow and second sample data related to configuration information of a plurality of nodes in the workflow framework; and training a workflow creation model based on the first sample data and the second sample data. A workflow creation task is divided into two types of sub-tasks, namely, a framework generation sub-task and a node configuration generation sub-task, so that the learning target of the model in each training stage can be clarified. In this way, the adaptation capability and creation quality of the workflow creation model in a real business environment can be improved.

Disclosed are methods, systems, and computer-readable media to perform operations including: A method for a cybersecurity risk assessment, including: acquiring information about business environment and business operations of a business entity; determining an engagement scope through facilitated sessions; performing cybersecurity control review and gap assessment to generate a control gap report and a control effectiveness report; performing cybersecurity threat analysis to generate an operational threat profile; performing a cybersecurity risk assessment to generate an operational risk profile; performing a business impact assessment to generate an operational impact profile; and providing the cybersecurity risk assessment to business sectors of the business entity.

The invention discloses a business integrated service platform and a data processing method applied by the business integrated service platform, and relates to the technical field of informatization services, and the business integrated service platform comprises a data fusion module which is used for converging cross-department business data of a full life cycle of an industrial project and constructing a unified full-chain electronic archive library; the supervision model module is used for establishing an industrial project digital monitoring model based on a full-chain archive library, monitoring key links of the project and generating a digital intelligent early warning signal; the service cooperation processing module triggers a flattening cooperation service instruction based on the digital intelligent early warning signal, generates a project blocking point problem and dispatches the project blocking point problem to a responsible department terminal; and the visual decision-making module is used for integrating the acquired investment attraction data, project progress data and approval efficiency data to obtain and display industrial layout, project performance and business environment trend analysis results. The invention discloses a high-efficiency industrial project supervision system capable of cracking data fragmentation dilemma and realizing full-period dynamic monitoring.

According to the data linkage display method and system based on natural language interaction, multi-modal natural language understanding, intelligent task matching and a front-end and back-end linkage control mechanism are fused, efficient, intelligent and low-delay interaction control between a mobile terminal and a data large screen is achieved, and the overall expandability and stability of the system are improved. Through a multi-modal natural language input mode, instruction understanding and tool selection are carried out in combination with a large language model, so that a non-professional user can also rapidly complete control operation on a data large screen through a natural language, the use threshold is remarkably reduced, after a rear end completes data processing, a control instruction is actively pushed to the front end of the large screen, and the user experience is improved. A user does not need to initiate a request again, the interface response speed is remarkably improved, meanwhile, operation tools are divided according to function categories, a dynamic loading mechanism is combined, related tool information is only input into a large language model when needed, the situation that context is overlong due to one-time input is avoided, and the adaptive capacity of a system in a complex service environment is improved.

The invention relates to the technical field of artificial intelligence and reinforcement learning, and discloses a cross-border trade intelligent decision optimization method based on reinforcement learning. The method comprises the following steps: constructing a composite state representation fusing tax, logistics, exchange rate, demand and competitive behavior; high-dimensional state compression is realized through an auto-encoder; designing a hierarchical action architecture to decouple a macroscopic strategy and a microscopic operation; a Nash equilibrium guided reward shaping function is introduced, and an equilibrium income deviation is estimated in combination with anti-factual reasoning; carrying out stable training by adopting a double-delay depth deterministic strategy gradient algorithm with state transition consistency constraint; an online fine tuning mechanism is deployed to adapt to a real business environment. According to the method, the strategy convergence speed, the annual profit rate and the responsiveness to policy mutation are remarkably improved.

Robust systems and methods are disclosed for fake account detection on digital platforms, integrating provenance analysis to scrutinize data origins, ownership, and history, thereby unveiling potential sources of fraudulent activities. They leverage dynamic feature generation, using advanced algorithms to assess user behaviors and interactions, ensuring the model stays attuned to the evolving landscape of cyber threats. Incorporating Quantum-assisted optimization, the method employs Quantum algorithms to expedite feature selection, enhancing detection efficiency. Quantum simulation further refines this process, creating sophisticated verification patterns and analytical techniques to distinguish genuine from fake accounts with higher accuracy. A comprehensive analysis amalgamates provenance data, telemetry, and dynamic features, forming a holistic detection approach. This system optimizes features through Quantum simulation, tailoring them to specific business environments, and deploys them via AI-ML DevOps, streamlining orchestration across various operational settings.

The invention relates to a financial risk control dynamic decision-making method, system and device and a medium. The method comprises the following steps: acquiring multi-source real-time risk characteristics and business environment indexes during customer transaction, and constructing an initial node structure associated with the characteristics through a graph neural network; effective connection is screened based on connection strength, and a dynamic routing scheme is generated by combining a high-risk scene optimization path priority; and utilizing reinforcement learning to iterate abnormal data flow analysis, and updating decision network configuration. The method comprises the following steps: extracting service demand indexes from configuration, generating an initial priority sequence through a graph neural network, harmonizing into a multi-target sequence by combining historical balance data, propagating risk characteristics in sequence to generate decision vectors, and verifying a matching degree to form a dynamic decision path. By adopting the method, the problem of insufficient scene identification of a traditional static model can be solved, the decision real-time performance is improved, the risk interception and business efficiency are balanced, a full-process dynamic risk control system is constructed, and efficient and adaptive risk decision support is provided for financial business.

The invention discloses a method, a device and a computer program product for mining an environment association rule of an electricity supplier, and the method comprises the steps: S1, collecting multi-source environment data of the electricity supplier, and carrying out the screening of a Delphi method to form a minimum data set of the association rule; s2, converting the minimum data set into a transactional database, and optimizing an Apriori algorithm by adopting a complete connection strategy and matrix vector space mapping to generate a frequent item set; s3, on the basis of the generated frequent item set, candidate association rules are generated by setting the threshold values of the minimum support degree, the confidence degree and the weight test coefficient, and the candidate association rules are filtered by applying a consequent constraint condition; and S4, constructing an analysis system integrated with the optimized Apriori algorithm, sorting the filtered association rules according to the priority order of the weight test coefficient, the confidence coefficient and the support degree, and visually outputting the sorted association rules. According to the method, the Apriori algorithm is improved, the multi-dimensional association rule in the electric power field is deeply mined, and electric power resource allocation is optimized.

The invention belongs to the technical field of load balancing, and discloses a printing equipment dynamic load balancing distribution method based on real-time order flow. The method comprises the following steps: acquiring order submission data streams distributed in a plurality of business areas in real time, and constructing an order traffic space-time heat matrix; obtaining an accumulated running time record, a historical fault maintenance log and a periodic maintenance record of each printing device, and dynamically evaluating a residual health life index; obtaining geographic coordinates of each business area and each printing device to form a time delay cost matrix; constructing an equipment load protection weight vector based on the residual health life index of each printing equipment, and carrying out dynamic fusion operation on the equipment load protection weight vector and the time delay cost matrix to generate a scheduling priority scoring matrix; according to the scheduling priority scoring matrix, a final printing task allocation result table is generated, and task scheduling is carried out; according to the method, the optimal scheduling effect can be always kept in a complex and changeable business environment, so that the printing service quality is improved.

The invention belongs to the field of data security, and discloses a financial business data risk early warning management method and system based on artificial intelligence, and the method comprises the steps: 1, obtaining a time sequence of an actual execution amount, and decomposing the time sequence of the actual execution amount to obtain an abnormal score of a budget item; step 2, acquiring an abnormal confidence score of the budget item based on the abnormal score, and judging whether the budget item is an abnormal budget item based on the abnormal confidence score; step 3, constructing a directed graph based on the business event data and the abnormal budget item; step 4, obtaining all paths which take the nodes with the abnormal budget as the end points and meet the path constraint in the directed graph, and obtaining a path set; respectively calculating a path score of each path; and 5, calculating a priority score of each path based on the path scores, obtaining a main path based on the priority scores, and generating a response suggestion based on the main path. According to the invention, the interpretation capability and the treatment capability of the financial risk early warning system in a complex business environment are improved.

The invention discloses a method for determining an optimal read-write strategy of an RAID card and a related product. The method comprises the following steps: acquiring an iostat echo field of the RAID card; performing feature extraction on the iostat echo field to obtain feature data; and performing feature matching on the feature data and an IO model library, and determining an optimal read-write strategy of the RAID card. According to the method, the extracted feature data and the IO model library which is pre-constructed and continuously optimized are subjected to matching analysis. And automatically recommending the most matched read-write strategy combination. According to the method, subjective errors caused by manual intervention are reduced, and the configuration accuracy and the adaptive capacity of the RAID card in a complex and changeable service environment are remarkably improved, so that the performance and the stability of a whole storage system are effectively improved.

1. Name of the Design Product: Mobile Phone with the Graphical User Interface of "Suishenban Enterprise Cloud". 2. Use of the Design Product: For running and displaying programs. 3. Design Key Points of the Design Product: Lies in the user interaction interface and display graphics on the mobile phone screen. 4. Picture or Photograph that Best Illustrates the Design Key Points: Front View. 5. The mobile phone has a conventional design, and the rear view, left view, right view, top view, and bottom view are omitted. 6. Use of the Graphical User Interface: The graphical user interface of this design product is used for the human-computer interaction interface of "Suishenban Enterprise Cloud". 7. Description of the Changing States of the Graphical User Interface: The front view is the main interface of "Suishenban Enterprise Cloud"; after human-computer interaction (clicking the "Enterprise Services" icon) on the front view, the interface change state diagram 1 is displayed; after human-computer interaction (clicking the "Enterprise-friendly Policies" icon) on the interface change state diagram 1, the interface change state diagram 2 is displayed; after human-computer interaction (clicking the "My Enterprise" icon) on the interface change state diagram 2, the interface change state diagram 3 is displayed; after human-computer interaction (clicking the "Shanghai Business Environment" icon) on the interface change state diagram 3, the interface change state diagram 4 is displayed; after human-computer interaction (clicking the "Tax Service Zone" icon) on the interface change state diagram 4, the interface change state diagram 5 is displayed.

A system is provided.SOLUTION: This system includes a means for automatically collecting customer information from an information source on the Internet, a means for analyzing the collected customer information and grasping the business environment and market trend of a customer company, a means for specifying the proposal need of the customer on the basis of an analysis result, a means for automatically generating a proposal material corresponding to the specified proposal need, and a means for transmitting the generated proposal material to a user terminal.SELECTED DRAWING: Figure 1

This invention discloses a knowledge graph-based intelligent question-and-answer method for audit guidance, relating to the field of digital auditing. Through knowledge graph framework design and ETL data warehouse technology, this invention extracts, cleans, and transforms audit business data relevant to business environment optimization audits, achieving the fusion of various business data to provide data support for intelligent question-and-answer. By constructing an intelligent question-and-answer system, and designing a multi-task-oriented approach based on real-world audit scenarios, it utilizes word segmentation, matching, and query modules to achieve knowledge graph-based intelligent question-and-answer for business environment optimization audit guidance. This reduces the workload of the audit process, freeing auditors from tedious and repetitive tasks, allowing them to focus more on risk identification, problem analysis, and root cause analysis, effectively improving audit efficiency and quality.

This invention relates to the field of artificial intelligence technology and proposes a deep AI-driven method for data anomaly detection and self-healing. The steps include: constructing a data governance and preprocessing platform to preprocess multi-source heterogeneous data and obtain high-quality data sources; employing a multi-algorithm fusion mechanism to detect anomalies in the data sources; constructing a dynamic modeling and self-learning engine to rapidly adapt model parameters based on meta-learning and to automatically search and optimize the model structure based on reinforcement learning to adapt to changes in data distribution and business environment; and providing an intelligent repair and self-healing mechanism for detected abnormal data, automatically correcting, repairing, and performing root cause analysis on data source anomalies, geographical location anomalies, data push failures, and system operation failures. This invention achieves high-precision detection of complex anomalies through a cascaded multi-algorithm fusion detection framework and realizes fully automatic model evolution through a collaborative adaptive engine of meta-learning and reinforcement learning.

This application provides a traffic prediction method and related apparatus, relating to the field of software technology. The method includes: acquiring the temporal traffic characteristics and interface spatial characteristics of a target interface; retrieving a trained traffic prediction model, wherein the traffic prediction model is obtained by iteratively training a basic model using the temporal traffic characteristics and interface spatial characteristics of a calibrated interface as training samples, with the goal of the predicted traffic of the training samples approximating its actual traffic; and inputting the temporal traffic characteristics and interface spatial characteristics of the target interface into the traffic prediction model to obtain the predicted traffic of the target interface. This application achieves high-precision prediction and reliability assessment of interface traffic in complex business environments, providing data support for resource scheduling and risk prevention.

The application discloses an intelligent WAF attack flow discrimination method, system, device and medium based on a large model MoE, belongs to the technical field of network security and artificial intelligence, and aims to solve the technical problem that an existing Web Application Firewall mainly relies on rule matching or a single model mode in an attack flow discrimination process, and it is difficult to effectively cope with diversified attack types, significant attack feature differences and dynamic business environment changes. The technical scheme is as follows: collecting Web access flow: collecting access request flow entering a Web application from a Web Application Firewall or a network environment where the Web Application Firewall is located through flow mirroring, bypass listening, log collection or interface calling; analyzing and preprocessing the access flow: analyzing and preprocessing the access request flow to generate structured request data; constructing a flow feature vector; discriminating attacks based on a large model of an MOE architecture; outputting an attack flow discrimination result; and executing a WAF protection strategy.