523results about How to "Improve good performance" patented technology

The invention discloses a multi-modal large model automatic evaluation method and system based on Agentic Workflow, relates to the technical field of artificial intelligence model evaluation, and solves the technical problems that an existing large model evaluation method lacks image-text evaluation, is relatively high in subjectivity and is easy to cause illusion. The method comprises the following steps that S1, an input task is analyzed, and a structured task template is generated; s2, generating a multi-round multi-modal task flow chart based on the task template generated in the step S1; s3, based on the flow chart in the step S2, distributing the multi-modal large model component to each task node, executing a task and obtaining an intermediate result; s4, performing multi-dimensional scoring on the intermediate and final results in the step S3 by a plurality of scoring Agents, and fusing to generate an evaluation result; and S5, generating a feedback report based on the process data in the steps S1 to S4, identifying a model short plate, and providing an optimization suggestion. The method has the advantages of comprehensive evaluation of multiple modes, real-time feedback optimization and the like.

The invention discloses a photovoltaic-energy storage-charging multi-stage scheduling and market bidding optimization method and a photovoltaic-energy storage-charging multi-stage scheduling and market bidding optimization device. The method comprises the following steps: constructing a data-driven random environment model reflecting photovoltaic output, electricity price fluctuation and charging load uncertainty by adopting a mode of combining time sequence clustering and a non-homogeneous Markov chain based on historical operation data; modeling a scheduling and bidding problem of the optical storage and charging integrated station into a multi-stage Markov decision process model which comprises day-ahead decision and joint optimization of multiple intra-day rolling adjustment; a deep reinforcement learning algorithm is utilized to train the network, and a strategy regulation and control network which can adapt to various uncertain scenes and meet equipment physical constraints is obtained; and deploying the trained strategy regulation and control network in an energy management system to realize global coordinated scheduling and bidding of the optical storage and charging integrated station. According to the method, the economic benefit is remarkably improved, the robustness is greatly enhanced, the decision is globally coordinated and optimized, the real-time decision capability is strong, and the expandability and portability are good.

The invention provides a multi-process-mode intelligent switching method and system for vehicle-mounted sludge treatment, and the method comprises the steps: carrying out the time-space alignment and standardization of multi-dimensional sensing data such as sludge characteristics, environmental parameters and equipment states, carrying out the real-time reasoning of a process switching critical value through combining with a lightweight incremental regression model, generating a self-adaptive threshold value band with a confidence interval, and carrying out the real-time reasoning of the process switching critical value. Dynamic monitoring and mode switching pre-judgment of actual operation parameters are realized; in the switching process, a weighted fusion progressive transition control strategy is adopted, the transfer rate is adaptively adjusted according to real-time feedback, the operation stability is guaranteed, and the intelligence, reliability and switching smoothness of process switching of the vehicle-mounted sludge treatment system are remarkably improved.

The invention discloses an anaphora disambiguation method and system based on big language model enhanced text and structured query language generation. The method comprises the following steps: receiving a natural language question of a user, and analyzing and generating structured table field information through mode information; identifying and rewriting fuzzy time expression in the problem; extracting ambiguous entities, and replacing the ambiguous entities with database standard values through semantic matching and fuzzy matching; synthesizing the information to generate a structured query language statement and executing the structured query language statement; and if the execution result is null, automatically triggering an anaphora disambiguation process, performing error correction and re-matching on field values in the statement through a dual matching mechanism, and generating and executing a corrected query statement. According to the method, the problems of fuzzy anaphora, indefinite time expression, low matching accuracy, resource waste and the like in a traditional SQL system are effectively solved through a strategy of combining pre-processing and post-processing, and the accuracy, robustness and execution efficiency of complex query are remarkably improved.

The invention belongs to the technical field of intelligent manufacturing and industrial scheduling, and provides a high-altitude platform multi-test task production scheduling method based on a clustering algorithm and multi-objective optimization, and the method comprises the steps: automatically calculating the exclusive resource demands of all working condition points in a plurality of aero-engine test tasks based on a multi-parameter coupling model; for each task, dividing a plurality of work packages by adopting a clustering algorithm based on the multi-dimensional features containing exclusive resource requirements in the task; a multi-objective model of multiple optimization objectives is constructed, all the work packages are jointly sorted globally, and the optimization objectives comprise the equipment utilization rate; and finally, under the condition that constraint of resource capacity, mutual exclusion of test cabins and task continuity is satisfied, allocating an available tester and a continuous time window to each work package, and generating an initial production scheduling plan. According to the method, the production scheduling efficiency and the resource utilization rate are effectively improved, the plan robustness is enhanced, and the method is suitable for high-complexity aero-engine test scheduling scenes.

The invention discloses a matrix type temperature detection system and method based on temperature-sensitive diodes, the problems of complex wiring and large temperature drift of a traditional multi-node temperature measurement system are solved through M * N matrix layout, row and column time-sharing gating and constant current driving technologies, the system adopts an independent column constant current source to ensure the measurement consistency, and a high-precision ADC and a dynamic calibration algorithm are combined, so that the measurement accuracy is improved. And the precision of + / -0.2 DEG C is realized within the range of 50-150 DEG C. The method is particularly suitable for high-density temperature measurement scenes such as battery thermal management, electronic equipment overheating monitoring and the like.

The invention provides a multi-reflection superposition enhanced microwave displacement measurement method and system, and the method comprises the steps: S1, constructing a microwave multi-reflection propagation path, enabling a microwave radar to transmit electromagnetic waves to the microwave multi-reflection propagation path as a transmission signal, and receiving a corresponding echo signal; s2, extracting length change information of a microwave multi-reflection propagation path according to the echo signal; s3, establishing a linear superposition relation model between the total length of the microwave propagation path and respective displacements of W reflection surfaces in the microwave multi-reflection propagation path; w2; and S4, based on the linear superposition relation model, displacement information of the corresponding reflection surface is obtained and output. According to the invention, a larger phase variation can be obtained under the condition of small displacement or weak vibration, so that the measurement sensitivity is improved and the signal-to-noise ratio is improved.

The invention discloses an engineering safety video generation method and system based on a generative large model. The method comprises the following steps of obtaining an application field and a theme requirement of a required engineering safety video; on the basis of application fields and theme requirements, a retrieval enhancement generation mechanism is adopted to retrieve in the multi-modal knowledge base to obtain related data, and a large language model is utilized to generate a training script copywriting; extracting cue words from the training script copywriting, and based on the cue words, generating a corresponding image by using a diffusion model; and converting the training script copywriting into an explanation audio, and finally synthesizing a virtual explanation video with synchronous mouth shapes by an audio driving model. The method can be suitable for a plurality of engineering scenes such as buildings, mining industry, tunnels, high-altitude operation and the like, has the characteristics of process automation, high content specialty, high generation efficiency and high cross-scene adaptability, and effectively improves the production efficiency and training effect of engineering safety education videos.

The invention discloses a method for optimizing key structure parameters of a deep well electric submersible pump based on performance simulation, and relates to the technical field of design optimization of electric submersible pumps, a three-dimensional geometric model of a deep well submersible centrifugal pump is built in advance, the three-dimensional geometric model comprises an impeller, a guide shell, a pump shaft, a pump shell, an upper connector, a lower connector and a full-flow-channel structure, and initial structure parameters are calibrated; and establishing a centrifugal pump simulation model based on a computational fluid dynamics technology, performing fluid domain extraction, grid division and grid independence verification on the three-dimensional geometric model, and setting fluid attributes, boundary conditions and a turbulence model. According to the method, a closed-loop iteration framework for simulation, optimization, evaluation and feedback is constructed by adopting a mode of coupling a computational fluid dynamics simulation technology and a genetic algorithm, the limitation of local parameter optimization in the prior art is broken through, systematic and collaborative optimization of key structure parameters of the submersible centrifugal pump is realized, and the method is suitable for large-scale popularization and application. And the efficiency of the optimization process and the final optimization effect are obviously improved.

The invention discloses an urban multi-unmanned aerial vehicle cooperative route planning method based on deep reinforcement learning, and the method comprises the steps: building a flight environment model based on urban three-dimensional point cloud data, and achieving the efficient obstacle query through an R-Tree index; for multiple unmanned aerial vehicles, acquiring distance information of surrounding obstacles by adopting a ray-based environment sensing mode, and constructing a state space containing a current unmanned aerial vehicle state, a target relative position, relative positions of other unmanned aerial vehicles and the distance information of the surrounding obstacles; outputting continuous flight control actions through a deep reinforcement learning strategy of parameter sharing; a multi-target reward function is designed, and the multiple unmanned aerial vehicles are guided to achieve safe and efficient collaborative route planning; in the execution stage, each unmanned aerial vehicle makes an independent decision only by depending on the shared strategy network and local observation information of the unmanned aerial vehicle, and distributed cooperative flight is realized. According to the method, the complexity of a traditional method for environment perception and decision calculation is effectively reduced, and the method is suitable for a multi-unmanned aerial vehicle planning task in a complex urban airspace.

The invention provides a cross-border trade supply chain risk early warning system based on digital twinning, and relates to the technical field of cross-border trade. The cross-border trade supply chain risk early warning system based on digital twinning comprises an entity layer, a data acquisition layer, a digital twinning modeling layer, a data processing layer, a risk early warning layer, a safety protection layer and an application output layer, and the entity layer is a monitoring object basis of the system and covers all key physical objects in a cross-border trade supply chain; comprising suppliers, logistics carriers, storage facilities, customs nodes and purchasers in the cross-border trade supply chain. The system integrates a multi-source data acquisition module, covers full-dimensional data of policies, logistics, finance, markets, Internet of Things perception and the like, ensures the comprehensiveness of risk factor extraction, improves the coverage of risk identification, greatly improves the accuracy and real-time performance of early warning, and solves the problem that a traditional early warning mode is inaccurate and lagged in evaluation.

The invention discloses an autonomous evolution type 5G protocol fuzzy test system based on a large language model, and the system comprises a protocol extraction unit which employs the large language model to analyze a 5G protocol specification document, and extracts structured protocol knowledge elements containing a message format, state machine logic and parameter constraints; the vulnerability analysis unit generates a potential vulnerability description list through big language model reasoning based on the knowledge elements; the test strategy generation unit drives a large language model to generate a targeted test case based on protocol knowledge, vulnerability description and historical test knowledge in the dynamic test knowledge base; the test execution unit executes the use case and captures a result; and feeding back an analysis result of the internalization unit, extracting a causal rule, generating new test knowledge and feeding back the new test knowledge to the knowledge base. According to the system disclosed by the invention, test targets and resources can be autonomously scheduled according to continuous updating of the knowledge base, so that the test process has an iterative optimization capability, and full-process automation and intelligentization of 5G protocol fuzzy testing are realized.

The invention discloses a wide-spectrum rapid scanning and intelligent identification method, system and device, and the method comprises the steps: firstly, carrying out the rapid frequency sweeping through employing a low-sampling-rate and low-quantization-precision receiver, generating a low-resolution time-frequency graph, and recovering the super-resolution of the low-resolution time-frequency graph into a high-resolution spectrum through a pre-trained deep learning model; then, the enhanced time-frequency image is segmented into time-frequency blocks, global features are extracted through a Transform encoder, and detection and screening of multiple candidate signal areas are achieved; and finally, carrying out directional sampling on the candidate region, respectively extracting time domain and frequency domain features, mapping the time domain and frequency domain features to a unified space for fusion, and completing signal category judgment based on the combined features and a judgment network. According to the wide-frequency-spectrum rapid scanning and intelligent identification method, system and device, through a layered architecture of broadband rapid scanning-frequency spectrum quality recovery-multi-region detection-directional sampling and time-frequency fusion identification, the reliability of unmanned aerial vehicle signal detection and identification in a complex electromagnetic environment is improved while the hardware cost is reduced.

The invention relates to the technical field of ferrous metallurgy casting, in particular to a drainage sand removing and recycling method and device. Comprising a mechanical arm, a lifting rotation controller, a controller arm, a sand suction cylinder, a sand conveying pipeline, a sand collecting tank and an injection pump. The lifting and rotating controller is fixedly mounted on the mechanical arm; the controller arm is connected with the lifting and rotating controller, and the lifting and rotating of the controller arm are controlled by the lifting and rotating controller; the sand suction cylinder is connected with the controller arm, the sand suction cylinder is of a U-shaped structure, and one end of the sand suction cylinder is a horn mouth used for sucking drainage sand; one end of the sand conveying pipeline is positioned above the tundish cover sprue gate, and the end part of the sand conveying pipeline is bent downwards to be connected with the other end of the sand suction cylinder; the other end of the sand conveying pipeline is connected with the sand collecting tank; the sand collecting tank is connected with an injection pump pipeline, and the injection pump provides suction power. The ladle filler sand, harmful gas in gaps of the ladle filler sand and a long nozzle and a small part of molten steel in contact with the ladle filler sand in a steel ladle can be discharged out of tundish molten steel and recycled.

The invention discloses a communication monitoring method and a communication system. The system comprises a monitoring module, a feature extraction module, a dynamic identification module, a behavior analysis module, an adaptive optimization module and a visual interface module. The monitoring module collects communication data flow through a mirror image port, the feature extraction module extracts packet length, time interval, direction sequence and encryption features by using a multi-dimensional feature fusion algorithm, and the dynamic recognition module realizes multi-protocol type recognition based on an improved self-attention convolutional neural network. The behavior analysis module constructs a communication relation graph and performs abnormal communication tracing; and the adaptive optimization module realizes model self-learning and parameter optimization through reinforcement learning. According to the method, through sliding window sampling, self-correlation analysis, entropy detection and GNN map modeling, accurate identification and behavior restoration of implicit traffic in a complex network environment are realized. According to the method, high-precision identification can be kept under the conditions of multi-protocol mixing and encrypted communication, and the characteristics of intelligence, self-adaption and expandability are achieved.

The invention relates to a Keystone-based deep ground security heterogeneous data fusion method and system, and the method comprises the steps: deploying a Keystone trusted execution environment on a deep ground edge computing node, creating a security enclave, carrying out the encryption access of multi-source heterogeneous data on the basis of remote authentication and key agreement, completing the space-time alignment and feature extraction after decryption in the enclave, and carrying out the fusion of the multi-source heterogeneous data. And performing cross-modal association analysis and risk assessment based on a preset model or a rule engine to obtain a fusion result, encrypting and signing the fusion result in the enclave, distributing the fusion result to an authorized receiver through a secure channel, and realizing one-time task destruction, long-term task cycle reconstruction and key refreshing in combination with enclave full life cycle management. According to the method, the credibility and the real-time performance of heterogeneous data fusion processing in a complex scene can be improved while the confidentiality and the integrity of deep operation and maintenance data are guaranteed.

The application provides a large model security management method, system, device and medium based on a core particle architecture, which can be applied to the technical field of semiconductor integrated circuits. The method comprises the following steps: setting a physically isolated special security core particle as a hardware trusted root in a heterogeneous integrated system, and connecting the special security core particle with at least one target core particle running a large model through a bus; deploying a lightweight security supervision model with a smaller parameter quantity than the large model in the special security core particle; collecting behavior characteristic data of the target core particle running the large model in real time; performing inference by using the lightweight security supervision model, calculating an abnormality metric between the current behavior of the target core particle and a preset normal behavior model; updating a dynamic trust state of the target core particle based on the abnormality metric; and performing a hardware-level security response operation by the special security core particle in response to the dynamic trust state reaching a predetermined threshold.

The present application belongs to the technical field of material corrosion data processing and industrial equipment state monitoring, and provides a kind of multi-source feature extraction and structured expression method of air conditioner heat exchanger corrosion data, specifically comprising the following steps: obtaining multi-source corrosion original data;Data preprocessing;Corrosion morphology feature extraction;Electrochemical feature extraction;Environmental influence feature extraction;Feature normalization processing;Structured feature vector construction;Form a structured feature vector with fixed dimension, unified expression. Each component in the feature vector corresponds to a corrosion-related parameter with clear physical meaning, completely describing the corrosion state, corrosion kinetics characteristics and service environment conditions of the heat exchanger under specific space-time conditions. Advantage: significantly improve the usability of data, provide an ideal data interface for multi-modal data fusion analysis and large model technology application, significantly improve the objectivity and reliability of the analysis results, have strong engineering practical value.

This invention provides a static parameter measurement device for overhead contact lines based on an unmanned aerial vehicle (UAV) platform, belonging to the field of railway overhead contact line inspection technology. It includes a UAV body with a laser measuring device mounted on its top and a telescopic support mounted on its side. The UAV body includes a processor chip, and the laser measuring device is connected to the processor chip. After takeoff, the telescopic support secures the UAV, and the laser measuring device measures the overhead contact line. The measured data is transmitted in real time to the processor chip for processing and analysis, ultimately achieving high-precision measurement of the static parameters of the overhead contact line. By linking the top-mounted laser measuring device with the processor chip, it is possible to conduct inspections and parameter measurements on conventional railway lines outside of designated maintenance windows, achieving high-precision, non-contact distance or terrain measurement, suitable for complex environments, and significantly improving data acquisition efficiency.

The application relates to a water quality change trend rapid prediction method based on multi-source data fusion and physical constraints, and specifically comprises the following steps: step 1: synchronously collecting data such as spectrum information, DO, COD, temperature and pH at key monitoring sites, constructing a water dynamics-water quality coupling equation, and simulating the space-time dynamic distribution of water quality parameters; step 2: outputting a water quality sensitive area through a water dynamics-water quality model, screening sensor layout points by combining information entropy evaluation and spatial clustering, realizing low-cost water quality sensor network deployment through a multi-objective optimization algorithm, and calculating a water body global water quality distribution map by adopting a spatial interpolation method; step 3: analyzing main pollution sources according to the synchronous collection of spectrum information at key monitoring sites, and adopting principal component analysis and an attention mechanism neural network; step 4: based on real-time optical characteristic value-DO data, combining a spatial topological network, a water quality gradient and a cross-region covariance to capture the spatial correlation of water quality parameters between different points, and constructing an optical characteristic value-DO-COD dynamic prediction model; combining pollution tracing and spectrum characteristic correction to correct the COD prediction value, adopting ensemble Kalman filtering to assimilate multi-source data, and improving the model accuracy.

The utility model belongs to the technical field of chemical equipment, and discloses a low-temperature dangerous chemical reagent storage cabinet. A low-temperature dangerous chemical reagent storage cabinet comprises a storage cabinet body, an equipment placement cabinet, a support, a cabinet door and a reagent placement table, the storage cabinet body is in a hollow shape with an opening in one longitudinal side, and the reagent placement table can be detachably installed in the storage cabinet body; the equipment placing cabinet is arranged below the storage cabinet body in a connected mode, cooling equipment can be placed in the equipment placing cabinet, and the support is arranged below the equipment placing cabinet in a connected mode. Through cooperative work of the heat absorber and the closed-loop water cooling system, rapid cooling is achieved, the low temperature in the cavity is maintained, the cooling device is suitable for chemical reagents sensitive to the temperature, the damping device effectively absorbs vibration of the cooling device, and collision between reagent bottles caused by vibration generated when the cooling device works is avoided.

This invention discloses a fault-tolerant multi-source fusion navigation and positioning method based on multiple solution separation, belonging to the field of integrity monitoring technology. The method includes steps such as constructing a risk fault tree model, dividing the fault mode set, parallel filtering positioning, spatiotemporal synchronization, robust fusion, and protection level calculation to address multiple risk sources faced by multi-source fusion navigation systems in complex environments. This achieves rigorous monitoring and elimination of risk sources from different sensors, ultimately obtaining a fault-tolerant positioning solution. This invention integrates integrity prior information with dynamic risk monitoring capabilities, constructing a highly robust and flexibly adaptable navigation and positioning framework that can ensure the integrity of multi-source fusion systems and meet the high-precision, high-safety requirements of intelligent transportation, unmanned systems, and other scenarios.

A power plant cable whole life cycle monitoring method based on whole-process identification and mobile terminal code scanning belongs to the technical field of cable monitoring. The method constructs a four-layer architecture of "perception layer-network layer-platform layer-application layer", uses Ecode128 coding of GB / T31866-2023 standard as the unique identification of the cable, and realizes whole-process identification binding by combining two-dimensional code and digital character combination identification carrier. The mobile terminal code scanning is used to realize paperless collection of field data, which is uploaded to the management platform based on the SpringBoot framework through 4G / 5G / Wi-Fi / data line and other transmission modes. The platform adopts front-end and back-end separation design, the back-end integrates SpringMVC and MyBatis-Plus, and the front-end realizes visual display through Vue.js. The function modules of design, construction, operation and maintenance, state monitoring and retirement are developed and designed, and the whole life cycle digital closed-loop management of the cable from design to retirement is realized. The present application effectively solves the technical problems of information dispersion, low efficiency, single monitoring and extensive management in the traditional cable management mode, and significantly improves the fine and intelligent level of cable management.

The application belongs to the technical field of positioning and measurement, and particularly relates to a target positioning method and device combining CSI coarse positioning and Y-type CCD fine correction, which comprises the following steps: S1, CSI acquisition equipment is arranged in a target area, and CSI data between a sending end and a receiving end is acquired; S2, a Y-type CCD sensor is geometrically calibrated and a coordinate system is corrected, and coordinate reconstruction is completed; S3, the CSI data is preprocessed, noise is removed, and input is normalized; S4, time domain features of the CSI are extracted by using a time domain branch; S5, frequency domain features of the CSI are extracted by using a frequency domain branch; S6, a gating fusion module is used to fuse the time domain and frequency domain features, and the approximate position coordinates of a target are output; S7, the Y-type CCD sensor is controlled to optically acquire a target area, and point light source coordinate information is acquired; and S8, error correction is performed on the data acquired by the Y-type CCD, and the accurate position coordinates of the target are output.

The utility model discloses a sorting and identifying device for large balls, small balls and plastic chip round cards, which comprises a main body frame, a ball guide hopper is arranged at the top end of the main body frame, a net opening metal plate is arranged on one side of the ball guide hopper, a push disc is arranged on the rear side of the net opening metal plate, and the ball guide hopper, the net opening metal plate and the push disc jointly form a primary sorting machine. An antenna and an antenna cover are respectively arranged at the top end of the main body frame, a bearing is arranged at the bottom end of the main body frame, a bearing fixing piece is arranged on the surface of the bearing, a motor rack is arranged at the bottom end of the main body frame, and a motor is arranged at the bottom end of the motor rack, so that the secondary sorting machine is formed. Through primary physical sorting and secondary intelligent identification, rapid and automatic sorting processing of large balls, small balls and plastic chip round plates is effectively achieved, size screening of materials with different diameters is achieved through combination of the ball guide hopper and the net opening metal plate, and the problems that the large balls are blocked, the small balls are not identified and the like are effectively solved.

The application discloses a cloud-edge coordination 5G networking multi-hop forwarding path dynamic processing method and a storage medium. The ant algorithm is used to optimize the forwarding lines between data base stations, so that the data transmission efficiency of the whole network is improved, and the data transmission delay is reduced. While ensuring the service quality, unnecessary data transmission distance and transfer are reduced, so that the operation and maintenance cost can be effectively reduced. The technical scheme adopted by the above embodiment of the application automatically optimizes path selection through an algorithm, and has good scalability and flexibility.

A kind of flow video active interaction control method, equipment and medium for the scene of helping blind, construct the hierarchical task system for the scene of helping blind, train the semantic understanding and behavior alignment of multimodal large model to specific task of helping blind;Introduce the active interaction control mechanism for flow video, under the premise of not changing the bottom model parameter, realize the trigger output of environmental perception by the dynamic suffix switching of determination mode and generation mode;Finally, the incremental context updating strategy is used to optimize the inference process, while keeping the timing consistency and reducing the calculation redundancy.The invention solves the technical problems of lack of special data, passive interaction logic and calculation redundancy of multimodal large model in flow environment through the synergistic effect of data-driven task adaptation and active interaction mechanism.The general framework proposed in the invention provides an important theoretical basis and technical paradigm for the paradigm evolution of flow video understanding from "passive analysis" to "active interaction".

The invention discloses a decision-making system and method based on a Dores database, and the system comprises a data access layer which is used for accessing multi-source heterogeneous financial data in real time, a Dores storage calculation layer, and achieves the data storage, column-type bucket separation and materialized view pre-calculation based on the Dores database; the visual application layer is used for providing bidirectional interactive financial data visualization and decision support; wherein the data access layer acquires data in real time through a streaming computing engine and transmits the data to the Dores storage computing layer, and the visual application layer performs real-time data interaction with the Dores storage computing layer through a two-way communication protocol. According to the method, the synchronous delay of financial data is shortened from 6 hours to 1 second, second-level real-time integration is realized, the aggregation query response time of billion-level data is reduced to be within 1 second based on a Dores column type storage and materialized view technology, the user interaction response delay is lower than 500 milliseconds through WebSocket two-way communication, and real-time adjustment of parameters and dynamic refreshing of a billboard are supported.

This invention discloses a hierarchical cryptographic service platform and method integrating QKD technology. The hierarchical cryptographic service platform includes a cryptographic service platform and at least one level of sub-cryptographic service platforms. At least one level of QKD network is built around the cryptographic service platform. Each level of the QKD network accesses an application system and / or connects to the corresponding level of the sub-cryptographic service platform. In this invention, the QKD network is built around the cryptographic service platform, which means that the QKD network can be built specifically according to application needs, giving full play to the ability of the cryptographic service platform to provide services for business applications. It is also easy to adapt and tailor according to business needs, and can be expanded on demand.

The application provides an intelligent question system based on a tool node cluster, which can be applied to the field of artificial intelligence technology. The method comprises the following steps: configuring a control center for storing table structure semantic information, model configuration information, communication addresses and database connection information; a workflow engine is used to respond to a natural language question request, obtain the communication addresses of tool nodes from the control center in sequence, and sequentially dispatch the tool nodes to execute processing tasks to obtain the response result of the natural language question request; the tool node cluster comprises at least a semantic conversion node and a data query node; the semantic conversion node is used to respond to a first dispatch instruction, convert the natural language question request into a structured query statement based on the language model corresponding to the table structure semantic information and the model configuration information; and the data query is used to connect a target database, execute the structured query statement, and obtain the response result of the natural language question request in response to a second dispatch instruction.