66 results about "Real time validation" patented technology

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses a generation optimization method and device based on dynamic verification feedback, equipment and a medium, and the method comprises the steps: pre-training a verification network used for analyzing and generating content quality; constructing a dynamic reward space containing orthogonal reward components; integrating the dynamic reward space into a generative model to form a real-time verification loop, and injecting verification signals into a plurality of processing layers; optimizing an exploration strategy of the generative model according to the verification signal; executing double-loop feedback control based on the real-time verification loop and the optimized exploration strategy, dynamically adjusting training parameters, and generating a target model; and outputting a reasoning result based on the target model. By constructing a real-time verification loop and an optimization strategy, a double-loop feedback control mechanism is realized, a verification signal is introduced into a training process, a training error and a strategy deviation are dynamically responded, and the training efficiency of the generative model is improved by combining rapid and slow adjustment paths.

The invention discloses a chip prototype verification method and device, a medium and a product, and relates to the technical field of integrated circuit verification, and the method comprises the steps: dynamically dividing a central processing unit core of a multi-core chip into a first core group and a second core group in a chip prototype verification platform; performing data interaction on the first core group and the second core group through the inter-core communication agent to obtain a verification control instruction; converting the test case into a chip register operation instruction or a real-time operating system drive call instruction based on the verification control instruction; distributing the chip register operation instruction to the first core group to execute a hardware real-time verification process, and distributing the real-time operation system drive calling instruction to the second core group to execute a multi-task scheduling verification process so as to respectively obtain a corresponding register snapshot and a task scheduling log; and aligning the register snapshot with the task scheduling log according to a time axis so as to generate a chip function verification result report based on the alignment data. Cooperative verification of bare computer verification and real-time operating system verification is realized.

The invention relates to the technical field of intelligent building AI construction monitoring, and discloses a high-rise building construction monitoring method and system based on intelligent AI. The method comprises the following steps: acquiring construction physical signals, and fusing to generate multi-dimensional state sensing information; constructing a digital twinborn body comprising a structure topology and a material parameter evolution path; deducing a construction process by using an AI agent, and outputting a risk situation map and a behavior intervention instruction set; and acquiring a field real-time resource state, carrying out matching verification on the instruction, and starting AI reconstruction on an unmatched instruction to generate a final executable instruction set. Through dynamic evolution modeling of material parameters, the structural state simulation and risk prediction precision is improved; through the real-time verification and reconstruction mechanism of the instruction, the performability of intervention measures is ensured, and closed-loop intelligent control from risk perception to accurate intervention is realized.

Computer-implemented system for real-time validation and threat mitigation for structured health transactions, including: a client policy repository that contains client-specific validation rules, consent restrictions, and risk thresholds; a trusted policy execution enclave that only allows policies and models after remote attestation of code and configuration, and decrypts and processes protected fields exclusively within the enclave; a grammatically aware streaming validator that enforces format and semantic constraints and synthesizes an auto-repair suggestion in case of parser errors, transforming inputs into a policy-compliant form with minimal changes; a hybrid risk engine that calculates rule-based and learned risk scores and furthermore evaluates a subset of features using data protection-preserving calculations to determine risk contributions without decoding selected fields; a causal graph generator that correlates related transactions over time into an entity-resolved, time-aligned graph and identifies impossibility patterns with edge-wise responsibility values; a coordinator for federated learning who updates models from client-local aggregates under differential privacy budgets and suspends aggregation when a distribution drift above a policy threshold is detected; an audit subsystem that generates zero-knowledge evidence demonstrating that selected compliance predicates for a transaction have been met without disclosing protected health information; a risk-adaptive flow control system that directs high-risk substreams into micro-quarantine sections with enhanced testing while maintaining the basic service quality for low-risk substreams; and a register that stores a validity context mark which links each decision to the identity of the policies, models, scope of consent and runtime environment used.

The invention discloses an automatic test method, system and device applied to a WSDL sending interface and a medium, and the method comprises the steps: associating a single test case into various scenes through a scene page preset parameter rule, and verifying the coupling between interface response and scene logic in real time during automatic execution; a WSDL interface definition and parameterization rule engine is dynamically analyzed, and automatic execution of multiple test cases is achieved; encrypted feedback data flow returned by an interface is captured in real time, key indexes are dynamically analyzed and extracted, automatic comparison and root cause tracing are carried out based on a multi-dimensional verification rule, and a test report is generated. According to the method, the problems that interface testing depends on manual coding, the process is split and the maintenance cost is high in aerospace engineering can be solved, zero-code rapid verification, forward and reverse closed-loop testing and interface change self-adaptive maintenance are achieved, and the aerospace software testing efficiency and reliability are remarkably improved.

The invention relates to the technical field of model design, in particular to a quality control method applied to hardware fitting three-dimensional model design. The method comprises the following steps that a hardware fitting three-dimensional design model is obtained; performing process sensitivity integration evaluation based on the hardware fitting three-dimensional design model to obtain fitting process sensitivity feature data; constructing an accessory process knowledge database based on the accessory process sensitive feature data; performing elastic deformation simulation on the hardware fitting based on the fitting process knowledge database to obtain hardware fitting deformation trajectory data; performing dynamic interference risk assessment and real-time verification based on the hardware fitting deformation trajectory data to obtain a fitting physical interference prediction result; and constructing an accessory process constraint rule based on the accessory process knowledge database. According to the method, seamless conversion from a three-dimensional model to an actual product can be ensured.

The invention provides a recruitment process global information screening and distinguishing method and system based on artificial intelligence, and belongs to the field of information system.The method comprises the steps that high-dimensional feature extraction and fusion are conducted on multi-source heterogeneous data through the quantum computing technology, and relevance feature expression is generated through a quantum entanglement encoder and quantum principal component analysis; a causal reasoning technology is combined, a super causal decision tree and an anti-fact causal network are constructed, dynamic modeling and optimization of the causal relationship are realized, and fairness and reliability of decision are improved through a resistance bias elimination module. In addition, the culture gene adapter is used for evaluating the matching degree between the candidates and the post and the organization culture, and the accuracy of the recruitment result is ensured. A meta-architecture evolutionary engine and a holographic verification sand table are introduced into the system design, automatic optimization and real-time verification of the model are achieved, and the efficiency and robustness of recruitment decision making are improved.

The invention discloses a hierarchical simulation modeling system for a new energy station cluster and a real-time verification method, belongs to the technical field of new energy power generation simulation, and solves the problems of high simulation calculation complexity, difficulty in real-time operation and closed-loop interaction verification with an external control system of a large-scale new energy station cluster. According to the technical scheme, the method comprises the steps that a digital dynamic real-time simulation platform configured with a multi-thread parallel computing architecture is adopted, and a new energy station detailed model comprising a wind power generation unit model, a photovoltaic power generation unit model, an energy storage power generation unit model and a current collection system model is deployed on the platform; generating an independent wind speed sequence for each fan through a wind resource distribution model; and constructing a large-base station cluster model composed of a plurality of station simplified models through aggregation equivalence. The system is mainly used for real-time simulation testing of a large-scale new energy base and closed-loop verification of a control system.

The invention provides a cross-platform workflow integrated circulation system, which comprises the following steps of: inputting corresponding data through an API (Application Program Interface) to ensure the correctness, integrity and consistency of the data; the source of the corresponding data can be from different information source platforms, the corresponding data is formatted or converted according to the requirements of the workflow integration system, and the workflow can be triggered after receiving and conversion are completed; the data are verified and cleaned in real time through the Apache Flink; asynchronously processing a message flow by using a message queue, and calling a task scheduling framework to distribute tasks in a model adopting a micro-service architecture; searching the registration service according to the defined file, and selecting the service with the best service quality; according to the method, the problems that an existing workflow integration system cannot adapt to loosely-coupled system application and cannot keep efficient and stable operation in a high-concurrency scene, and then normal work of an enterprise is affected are solved.

The invention discloses a method for seamlessly handling business in an interactive interface, a medium and equipment. The method comprises the following steps: receiving a user business request and loading a business rule containing a process state machine; guiding a user to input information according to the current process stage, and dynamically generating a structured confirmation component after real-time verification; monitoring user confirmation operation to form a confirmed information unit; inquiring a process state machine based on the confirmed information unit to judge a stage transition condition, and executing interface reconstruction operation when the condition is met; and when the final stage is reached and all necessary information fields are confirmed, automatically packaging and submitting a complete data request packet, and displaying a handling result on the same interface. According to the method, the problem of flow interruption caused by multi-interface jump in traditional business handling is solved, the continuity of user operation and the interface consistency are ensured through state machine driving and dynamic interface reconstruction, and the business handling efficiency and the user experience are remarkably improved.

The invention discloses a hybrid electric vehicle thermal management system mechanism-data hybrid drive modeling method, and belongs to the technical field of new energy vehicle thermal management, and the method comprises the steps: obtaining sample data under an optimization purpose; performing mechanism-data hybrid modeling on subsystems of the thermal management system of the hybrid electric vehicle to obtain modeling results of different subsystems; performing model integration on the modeling result to obtain a system model; and the system model is verified and optimized in real time through sample data, and an optimized system model is obtained for thermal management of the hybrid electric vehicle. According to the technical scheme, high-precision dynamic modeling, global energy efficiency optimization and dynamic real-time control of the thermal management system of the hybrid electric vehicle can be realized.

The invention discloses an internet of things simulation method, device and equipment, a storage medium and a product, and relates to the technical field of simulation, and the internet of things simulation method comprises the following steps: responding to a simulation execution request, running a communication process in a function agent equipment node and a simulation virtual environment, and obtaining a communication result, the function proxy equipment nodes comprise static behavior nodes and dynamic behavior nodes, and the dynamic behavior nodes can adaptively adjust communication parameters; and visually displaying the communication result on a graphical interface. According to the method and the device, after the simulation execution request is received, the communication process is operated in the function agent equipment node and the simulation virtual environment to obtain the communication result, and the communication result is visually displayed on the graphical interface; and the dynamic behavior nodes can adaptively adjust communication parameters, so that the real effect of the adaptive algorithm can be verified in real time.

The invention provides a real-time verification and feedback method and device for a natural language low-code platform, relates to the field of natural language processing, and solves the technical problem that an existing low-code development platform generally lacks a real-time verification mechanism for generated codes. The method comprises the following steps: acquiring business demand data; converting the business demand data into structured data through a BERT model, wherein the structured data comprises an execution sequence, conditional constraints and a business logic mapping relation of each process node; generating a decision tree based on the structured data; based on the decision tree and the structured data, generating a corresponding low-code script through a generation model; submitting the low-code script to an execution engine, performing real-time execution verification in a containerized isolation environment, and outputting a verification result and a running log; and analyzing the verification result and the running log, generating natural language feedback information, and optimizing the generation model. The method and the device are used in the real-time verification and feedback process of the natural language low-code platform.

The invention relates to the field of chip-level security technology and electric digital data processing, and discloses an anti-interference low-power consumption random number generation and real-time verification method and system, and the method comprises the steps: collecting multi-source entropy data and environment monitoring data in parallel, dynamically adjusting the weight of an entropy source according to the environment data through a cooperative scheduling mechanism, and carrying out the real-time verification of the entropy source; according to the method and the system, the real-time verification result and the task priority are linked to regulate and control the power consumption of the system, and hardware verification and exception interception are completed before the random number is output, so that the generation of the random number is converted from static preset configuration into a dynamic self-reconstruction process capable of actively adapting to the change of the external environment; the core security comes from the dynamic adaptation capability of the whole multi-source system instead of the robustness of a single entropy source, the matching between the system power consumption input and the security output is realized, and the stability and the reliability of the random number in a complex embedded scene are improved.

This invention belongs to the field of data processing technology, and in particular relates to a cross-system risk data fusion method and system based on federated learning. This invention solves the defect of one-size-fits-all aggregation in traditional federated learning by dynamically adjusting weights based on real-time verification indicators and data volume, so that high-value data can automatically obtain higher contributions. Under the premise of not sharing the original data at all, it achieves a faster response speed than centralized training through encrypted aggregation and dynamic weight allocation.

The invention discloses a dynamic generation and verification method for an access data model of information protection equipment, relates to the technical field of data verification, and effectively improves the accuracy of equipment data and the self-adaptive capability of a system through real-time verification and self-correction behavior monitoring of the access data of the equipment. According to the method, the self-correction behavior can be found and adjusted in time when the equipment is abnormal, error correction is prevented from being brought into a system data model, and error evolution and instability of the system model are avoided. Especially in the self-correction process of the equipment, the rationality of the correction behavior is judged in real time by dynamically calculating the correction behavior index and comparing the correction behavior index with the preset threshold value, so that the system can quickly cope with equipment faults or data anomalies, and performance reduction, data inconsistency and system instability caused by wrong correction are avoided; the problem that the self-correction behavior of the equipment cannot be effectively monitored and verified in the prior art is solved, and the reliability of the equipment access data model and the robustness of the system are enhanced.

Techniques for improved data and / or resource validation provide a real-time validation of data and resources. A resource may include an aggregation of related data into a single unique unit. The validation may be performed based on one or more events or triggers, such as on the occurrence of a data change, deployment of an application, when the resource(s) are utilized, etc. The validation may be on demand (e.g., based on one or more events and / or triggers) and / or manually (e.g., via a call via an application program interface by a user).

The invention relates to the technical field of artificial intelligence and block chains, and discloses an AI model production optimization system based on a block chain and meta-universe data tagging, and the system comprises a block chain network module which is used for carrying out the distributed storage of a hash value of tagged data generated in a meta-universe environment and related metadata, automatic verification and access authority control of the marked data are realized through the smart contract; and the zero-trust architecture module is integrated in the block chain network and is used for verifying the legality of the access request in real time and adjusting the access authority of the user according to the dynamic authority management strategy in the block chain. Distributed storage and consensus verification of meta-universe data are realized through the block chain network module, backup and consistency of the data on multiple nodes are ensured, integrity and authenticity of all recorded data and operation logs are ensured due to non-tampering of a block chain, the risk that the data is tampered is effectively prevented, and the data storage efficiency is improved. Therefore, the security of data management is improved.

The invention is suitable for the field of modular learning, and provides a modular learning method and system for bid and purchase laws and regulations, and the method comprises the steps: decomposing bid and purchase legal terms into basic element modules and application scene modules, forming an initial module library, loading laws and regulation module versions in different periods and regions, and carrying out the multi-dimensional space-time adaptation; collecting module calling combination operation of a user, verifying compliance in real time based on association rules and generating combination operation data; a user operation track is recorded, module association degree parameters are dynamically adjusted in combination with related data, an evolutionary knowledge network is constructed, and association rules are updated; and synchronously outputting the visual knowledge graph to display the module relationship and the learning progress. According to the invention, refined learning and multi-dimensional adaptation of laws and regulations are realized, individual cognitive features can be reflected, learning efficiency and pertinence are improved, and the method is suitable for the field of bid procurement laws and regulations learning.

We provide the system. [Solution] A means of presenting procedural information using a generative model, A means of verifying user input in real time, A means of automatically generating application documents based on a standardized format, The means of transmitting the application documents to the administrative agency, A system that includes this.

The invention relates to the technical field of electrical digital data processing, and discloses a form filling method based on a tree forest structure, which is characterized by comprising the following steps of: acquiring multi-source form data, converting the multi-source form data into semantic vectors by using a pre-training language model, and constructing a two-dimensional incidence matrix by combining co-occurrence frequency analysis and correlation strength calculation; dynamically constructing a tree forest containing conflict detection; according to the form type filled by the user, in combination with a caching strategy of a session mode or a historical mode, matching and processing conflicts according to meta-information vector priorities; the forest node relation is adjusted through a visual platform, and the association accuracy is verified in real time; and monitoring the modification rate to trigger incremental learning, and iterating the forest structure according to a service isolation strategy. The problems of time consumption, field conflict, repeated labor and poor user experience of form filling in the prior art are solved, and the purposes of intelligent multiplexing, efficient filling, conflict avoidance and experience improvement are achieved.

This application relates to the fields of artificial intelligence security and software copyright protection technology, and discloses a method and system for the encrypted deployment and operation control of large models. The method includes: loading an encrypted large language model file on the deployment end and starting a model inference service; executing parallel environment monitoring tasks during the operation of the model inference service to verify the matching status of the current operating environment with preset authorization conditions in real time; when the verification matching status is abnormal, maintaining the process running state of the model inference service and its interface response capability to external requests, while switching the operating mode to a controlled interference mode; in the controlled interference mode, intercepting intermediate probability distribution data during the model inference calculation process and executing a computational perturbation strategy to disrupt the semantic logic of the model-generated content, thereby achieving implicit degradation of the output results. This application significantly improves the concealment and resistance to reverse engineering of the authorization protection mechanism.

The invention discloses a coordination control method, system and device for a multi-machine parallel SVG and a storage medium, and relates to the technical field of dynamic reactive compensation of a power system, and the method comprises the steps: employing a chain SVG circuit topological graph, constructing a direct-hanging SVG simulation model, and carrying out the simulation analysis to make a control strategy; a control strategy real-time verification platform is constructed to verify the control strategy, a communication conversion protocol of the SVG control system is converted into a real-time simulation communication adaptation protocol supported by the simulation system, and early-stage principle verification is completed; a rotating coordinate system PI double-closed-loop grid-connected control strategy is adopted, reactive current loop setting is generated, a coordination control strategy is executed in a multi-machine parallel connection scene, reactive hedging is restrained, and dynamic response is unified. According to the method, reactive current loop setting is generated by adopting a rotating coordinate system PI double-closed-loop grid-connected control strategy, and unified setting and consistent response with current inner loop rapid tracking and outer layer reactive target mapping as the core are achieved.

The invention is suitable for the technical field of games, and provides a game issuing self-service access method, system and device and a medium, and the method comprises the steps: obtaining access application data of a game research and development party, and carrying out the verification and technical analysis of the access application data, and obtaining an interface configuration file; based on the interface configuration file, determining an interface calling logic, and generating a docking interface test set; calling a game docking test interface based on the docking interface test set, and generating a docking verification result; performing interface operation state verification on the docking verification result by adopting a real-time verification state monitoring algorithm to generate verification state information; updating a docking progress data table based on the verification state information; and synchronizing the updated docking progress data table to the game research and development party and the game issuer. According to the method, automatic verification of the game access process is realized, the game access process is simplified, the access efficiency and accuracy are improved, and powerful support is provided for game issuing and operation.

The application discloses a wind-solar-hydrogen coupling hydrogen production control method and system based on deep reinforcement learning, first, wind-solar-hydrogen related data is collected and feature extraction is carried out, and the LSTM model and the LSTM-Transformer model are used for multi-time scale power prediction at the day level, the hour level and the minute level; then, a multi-objective reward function combining hydrogen production income, equipment loss and carbon emission is used in combination with the DDPG algorithm to output an optimal control strategy; finally, multi-time scale control is carried out based on a three-layer scheduling framework of the day level, the hour level and the minute level, and the optimal control strategy is verified in real time by using the PINN. The application is based on wind-solar-hydrogen related data, uses the DDPG algorithm to realize accurate control of a continuous action space, the multi-objective reward function guides the DDPG learning to consider the optimal strategy of economy, life and carbon emission, a three-layer scheduling framework of the day level, the hour level and the minute level is constructed to realize multi-time scale collaborative optimization, and the PINN hybrid modeling is used to reduce simulation delay and meet real-time control requirements.

The invention discloses a water conservancy and hydropower construction resource management scheduling method and system based on artificial intelligence, relates to the technical field of resource management scheduling, and provides the following scheme: preprocessing real-time state data and environmental parameter data to obtain a standardized data transmission object; inputting the processed data into an artificial intelligence dynamic association model for processing, and generating a risk level of the equipment; when the risk level of the equipment reaches a preset value, triggering an adaptive scheduling instruction, and generating a structured scheduling instruction packet based on a construction progress model and equipment position data; and issuing the structured scheduling instruction packet to a standby equipment execution end, and verifying the equipment health index change under the new instruction packet in real time. By constructing an equipment environment dynamic association model, the equipment fault risk is predicted by artificial intelligence, and an adaptive scheduling instruction is triggered, so that the problem of resource scheduling lag caused by equipment damage due to environment sudden change in water conservancy and hydropower construction is solved.

The invention provides a block chain-based data product registration management method, which comprises the following steps of: in response to manual auditing verification, marking a data product with metadata compliance as passing auditing; carrying out encryption processing on metadata of the data product; calling a block chain uploading interface, and packaging the encrypted data to a to-be-confirmed block; returning a unique evidence ID as an on-chain identifier; obtaining a complete hash value of the corresponding transaction based on the evidence ID; and storing the hash value and embedding the hash value in a certificate. According to the method, a transaction hash is embedded into a product registration certificate, a real-time verification mechanism on a chain is realized, and deep integration of a long safety chain and a certificate system is relied on: the transaction hash is generated by a long safety chain consensus mechanism and forms a binding relationship with metadata, and hash formats of other block chain systems cannot be matched with verification logic; certificate hash and on-chain metadata are quickly compared through a Changsafety link interface, and high-efficiency closed-loop verification is realized based on API design and consensus rules of the Changsafety link.

Real-time validation of microcode updates may include: executing a workload on at least one first processor having a first version of a microcode instruction set; executing the workload on at least one second processor having a second version of a microcode instruction set, wherein the second version of the microcode instruction set comprises an update of the first version of the microcode instruction set; and validating the second version of the microcode instruction set based on a comparison of output from executing the workload using the at least one first processor and output from executing the workload using the at least one second processor.

The application relates to the technical field of building information modeling and discloses a double-layer foamed ceramic wallboard advanced hole reservation BIM collaborative design method, which comprises the following steps: after receiving a design operation, a preprocessing transaction is generated; localized real-time verification is performed based on internal constraint rules of components to provide instant feedback; after verification, it is determined whether distributed negotiation needs to be started based on external influence rules; if so, potential influence notifications are broadcast to affected participants, and negotiation responses including approval, rejection or approval with conditions are collected; and the responses are comprehensively judged based on preset adjudication rules to determine the final disposal result of the preprocessing transaction. Through the pre-verification and negotiation mechanism, the traditional post-conflict resolution is moved forward, the strong consistency of model data and the traceability of design decisions in a multi-user environment are ensured, and the efficiency and quality of collaborative design are effectively improved.

The invention discloses a form filling recommendation method and device, equipment and a storage medium, and relates to the technical field of job automation, the form filling recommendation method comprises the following steps: performing form access configuration according to a form column, a form data source and a column filling logic to obtain form filling configuration; performing configuration matching according to a form filling requirement and the form filling configuration to obtain current form configuration; and performing parallel filling recommendation according to the current form configuration and the form filling model to obtain form filling recommendation data. By configuring form columns, data sources and column filling logic, performing real-time verification and continuous adjustment on a configuration effect and deploying configuration with the best operation effect, production real-time form recommendation filling is realized, recommendation values of all the columns are given at a time by concurrently executing a recommendation process, response time is irrelevant to the number of the columns, and real-time form recommendation filling is realized. And the energy efficiency of filling the form by the office is improved.