70 results about "Feedback analysis" patented technology

The invention discloses a supply chain quality collaboration method and system based on a block chain, and relates to the technical field of block chain and supply chain quality management, and the method comprises the steps: collecting quality events according to a batch quality collaboration baseline table, generating a credible collection proof package and a to-be-verified quality event queue, executing dynamic endorsement verification, and writing the dynamic endorsement verification into a quality event account book, outputting a batch state table and an under-chain evidence pointer; performing rapid detection and judgment based on the batch state table and the under-chain evidence pointer, generating a pre-release report and establishing a pre-release mapping table; and triggering a difference correction contract according to the pre-release mapping table, updating the batch state table, generating a collaborative work order, pushing a quality collaborative strategy instruction, and outputting a quality collaborative closed-loop record. According to the method, the risk feedback analysis result table is generated by auditing and evaluating the quality collaborative closed-loop record, the risk layering strategy table is revised, and the batch quality collaborative baseline table is updated, so that the key field constraint is continuously calibrated, and the traceability and consistency of collaborative processing are improved.

The invention relates to the technical field of knowledge fusion, and discloses an interactive health science popularization question and answer guidance system for constructing a medical knowledge graph, comprising: a guidance instruction generation module extracting attribute variation dimensions between to-be-aligned data and candidate nodes and generating a guidance instruction; the feedback analysis module converts the feedback data into a feedback correction vector; the atlas fusion actuator determines an initial fusion weight according to the coordinate distance, determines a weight correction coefficient based on the topological centrality of the target node, constructs a weighted feature update function by using a feedback correction vector and a local topological relation to calculate a feature increment, and completes feature convergence fusion; according to the method, a priori constraint force balance feedback feature pointing value provided by a map structure is utilized, it is ensured that heterogeneous knowledge fusion conforms to medical ontology logic, and the global stability of science popularization map evolution is guaranteed.

The invention relates to the technical field of semantic analysis, can be applied to business scenes such as financial science and technology and medical health, and discloses a bidirectional cue word collaborative optimization method, device and equipment and a medium. Generating a dialogue response set with a dialogue content input language model, and obtaining a feedback analysis result; determining an optimization operation type according to the uncertainty index, and updating the system cue word and the user cue word to obtain an updated cue word combination; and storing the updated cue word combination into a cue word memory library, and retrieving candidate cue word combinations from the cue word memory library for use in new task processing. Through an uncertainty-driven bidirectional cue word collaborative optimization mechanism, semantic consistency, dynamic adjustability and reusability among cue words are realized, so that the model has higher adaptability and generalization ability, and the task processing quality and efficiency are improved.

The present application relates to a multi-agent collaborative product closed-loop optimization system and method based on user feedback data, which is used to solve the technical problem that the existing technology cannot efficiently utilize user feedback data to obtain optimization improvement requirements, resulting in poor optimization effect. It includes: a data collection module that captures user feedback data in real time from public and private data sources; a data analysis module that calls a multi-dimensional analysis agent to perform AI multi-dimensional analysis and mining on the user feedback data after data normalization, generating feedback analysis results; an image construction module that constructs and calls expert role prompt information templates, fills in the context by inputting feedback analysis results into the templates, obtains expert role prompt information, and calls an intelligent portrait generation agent to construct a structured user intelligent portrait; a task generation module that calls a business design expert agent to automatically generate product optimization requirements and task collaboration based on feedback analysis results and structured user intelligent portraits.

The embodiment of the application discloses a method and system for detecting the state of a bone conduction hearing device, the bone conduction hearing device at least comprising a microphone, a speaker, a feedback analysis unit and a signal processing unit, the method comprising: generating a third sound by the speaker based on a first signal; wherein the first signal is generated by the signal processing unit; receiving the third sound by the microphone and generating a feedback signal; determining, by the feedback analysis unit, the feedback path transfer function from the speaker to the microphone of the bone conduction hearing device based on the feedback signal of the microphone and the first signal; obtaining at least one preset feedback path transfer function; comparing the feedback path transfer function with the at least one preset feedback path transfer function; and determining, by the signal processing unit, the state of the bone conduction hearing device according to the comparison result.

The application discloses a kind of simulation exercise devices for preventing dysphagia of cerebral apoplexy patient, it is related to cerebral apoplexy patient swallowing simulation technical field, including: placement bottom plate, adjustable dysphagia exercise mechanism and feedback analysis mechanism, adjustable dysphagia exercise mechanism is located in the right side of feedback analysis mechanism, adjustable dysphagia exercise mechanism: adjustable dysphagia exercise mechanism includes adjustable exercise component for swallowing mastication exercise intensity adjustment, by adjustable dysphagia exercise mechanism adjustable exercise component And the setting of flexible sensitivity promoting component, it is different from the function of rehabilitation training equipment in the prior art is relatively single, and the training device is replaced back and forth during rehabilitation training, and the linkage of training between devices cannot be guaranteed, effectively achieve when mastication training, patient lip and tongue are trained simultaneously with sensory force, close to life, effective simulation, better effect.

The invention discloses a dynamic test platform and a dynamic test method for a composite energy storage system based on cooperative interaction. The dynamic test platform comprises a flywheel energy storage unit, a compressed air energy storage unit, an energy management and cooperative control unit, a data acquisition and analysis unit and a grid-connected / off-grid mode main switch, the energy management and cooperative control unit is used for dynamically adjusting the running states and function roles of the flywheel energy storage unit and the compressed air energy storage unit; the data acquisition and analysis unit is used for acquiring full-dimension operation state parameters of the flywheel energy storage unit and the compressed air energy storage unit in real time so as to identify abnormal working conditions and feed back analysis results to the energy management and cooperative control unit, and a control strategy is optimized; and the grid-connected / off-grid mode master switch receives a switch control signal of the energy management and cooperative control unit so as to switch the operation mode of the composite energy storage system and perform electric energy exchange. High-precision and multi-mode dynamic testing between the two large energy storage systems is achieved, system performance can be evaluated, and a collaborative operation strategy can be optimized.

The invention relates to the technical field of modern communication, and discloses a wireless network card power adaptive control method and system. The method comprises the following steps: acquiring real-time interference data, performing spectrum change according to the real-time interference data to obtain an interference intensity distribution diagram, performing interference correlation analysis and power optimization calculation according to the interference intensity distribution diagram to obtain a power configuration scheme, performing parameter updating according to the power configuration scheme to obtain a preliminary power correction result, and performing power optimization calculation according to the preliminary power correction result. The method comprises the steps of obtaining a preliminary power correction result, carrying out interference comparison evaluation according to the preliminary power correction result to obtain deviation information, carrying out power optimization according to the deviation information to obtain an optimized power configuration scheme, and carrying out synchronous configuration and index feedback analysis according to the optimized power configuration scheme to obtain a final regulation command set. According to the method, the problem that interference chain reaction is easily caused by equipment power adjustment can be solved, so that stable communication and interference suppression in a complex network environment are realized.

The invention relates to the technical field of construction safety early warning, in particular to a construction safety early warning system and early warning method adaptive to a smart building, the system comprises a construction safety early warning center, and an access management unit, a construction protection unit, a personnel monitoring unit, a personnel construction unit and a construction management unit are arranged in the construction safety early warning center; according to the method, analysis is preliminarily carried out from the angle of entry of the target construction site, non-constructors are prevented from entering the construction site, the safety of the construction site is improved, analysis is further carried out from two points of high-altitude protection and ground protection, the construction protection risk is reduced, and the construction safety is improved. Personnel safety early warning feedback analysis is carried out in an information progressive mode, the probability of occurrence of safety accidents is effectively reduced, analysis is carried out deeply from the environment where the constructors are located and the equipment used by the constructors, whether potential safety risks exist in the construction stage of the constructors or not is further analyzed, and the safety of the constructors is improved. And targeted management can be conveniently carried out in time.

The invention provides a data annotation system and method based on a large language model, a medium and a terminal, and the system comprises a data access layer which is used for collecting to-be-annotated data, and carrying out the preprocessing of the to-be-annotated data, so as to enable the to-be-annotated data to be converted into a unified data format; the intelligent annotation engine layer is used for retrieving context information of a vertical field for the received to-be-annotated data in the unified data format, splicing the retrieved context information and the to-be-annotated data and then inputting the spliced information and the to-be-annotated data into a plurality of pre-trained large language models; the large language model is used for generating a labeling result of the to-be-labeled data; and the quality control layer is used for monitoring the quality of the labeling results generated by the plurality of large language models and carrying out feedback analysis according to the monitored labeling quality problem. According to the method and the device, the automation of the whole process from the acquisition of the to-be-labeled data to the generation of the labeling result can be realized, the vertical domain knowledge is integrated, the labeling result is strictly controlled, and the process is continuously subjected to feedback optimization.

The system according to this embodiment aims to generate optimal work procedures and provide training by utilizing accumulated work procedure manuals and on-site feedback. [Solution] The system according to the embodiment comprises a collection unit, an analysis unit, and a training unit. The collection unit collects accumulated work procedures and on-site feedback. The analysis unit analyzes the information collected by the collection unit and generates the optimal work procedure. The training unit provides training based on the work procedure generated by the analysis unit.

Generating visual workflow representations by receiving data including text instructions, identifying actions in the instructions, generating a mapping of the actions according to a generative model, the mapping including an action sequence, providing the mapping to a user, receiving feedback from the user, altering the generative model according to the feedback, and generating a revised mapping according to the feedback.

We provide the system. [Solution] A data analysis means for collecting and preprocessing surveys, emails, chats, and meeting records, A personality trait evaluation means that uses a generative AI model to perform a process that objectively evaluates the user's personality traits and skills, A personnel placement recommendation tool that calculates the optimal team structure and staffing based on evaluation results and creates a specific placement plan, A feedback analysis tool that analyzes user-provided feedback to evaluate actual performance and team harmony, A database update mechanism that updates personality profiles and skill maps based on feedback and newly collected data, A system that includes this.

The invention provides a dynamic response type cloud platform for chronic disease self-management, and relates to the technical field of artificial intelligence. Comprising the steps that physiological data of a user are collected in real time through a data collection module, health management suggestions are generated through a data analysis module, medical literatures and user feedback are integrated in combination with a knowledge graph module, and a personalized health management suggestion report is provided. The user interaction module realizes real-time data display and feedback, the feedback analysis module generates a user portrait, the data packaging module generates packaged data, and the large model reasoning module quickly updates a health management suggestion report. And the cloud infrastructure module ensures data storage security and access control, so that the health management experience of the user is improved.

An object of a system according to an embodiment is to improve service experience by responding to an inquiry from a customer immediately and on a 24-hour basis.SOLUTION: A system according to an embodiment includes a natural language processing unit, a learning unit, a transfer unit, a translation unit, an aggregation unit, and a feedback analysis unit. The natural language processor uses natural language processing to understand the intent of the customer's question and generate an appropriate answer. The learner evolves to provide optimal answers from past dialogues. The forwarder automatically forwards the complex query to a human operator. The translation unit supports multiple languages, allows a customer to ask a question in his / her native language, and automatically translates the question to provide an answer. The aggregation unit aggregates inquiry leads of a plurality of services into one application. The feedback analyzer automatically analyzes the feedback from the customer and sends it immediately to the product.SELECTED DRAWING: Figure 1

The application relates to the field of civil engineering and relates to an intelligent perception test model and method for vertical bearing capacity of a pressure type anchor rod foundation, which comprises the following steps: integrating high-precision sensors at key positions of a to-be-tested device, collecting data of the to-be-tested device through the sensors, and extracting characteristic parameters; constructing an evaluation model for vertical bearing capacity of the pressure type anchor rod foundation based on an artificial intelligence algorithm according to the characteristic parameters, and obtaining evaluation data of the vertical bearing capacity of the pressure type anchor rod foundation; and establishing a feedback analysis mechanism according to the evaluation data of the vertical bearing capacity of the pressure type anchor rod foundation, automatically triggering a warning mechanism when the evaluation data is abnormal, and giving an optimization scheme. The application solves the problem that the test model, intelligent perception and feedback analysis are not integrated when evaluating the vertical bearing capacity of the pressure type anchor rod foundation.

A system is provided.SOLUTION: Generating means for generating individualized health advice and health plans based on the analyzing means, integrating means for incorporating the health plans into gamification elements, providing means for providing the generated health advice and plans to users, and receiving feedback from the users, wherein the generating means generates the individualized health advice and health plans based on the generated health advice and health plans, and the analyzing means analyzes the generated health advice and health plans using a generated AI model. A system comprising: feedback transmission means for transmitting the feedback data to a server; and feedback analysis means for analyzing the feedback and generating updated health advice and plans.SELECTED DRAWING: Figure 1

The invention relates to the technical field of public service platforms, and particularly provides a development method of a public service platform based on SaaS and cloud computing, which comprises the following steps: aggregating discrete demand units into a dynamic demand map with a topological structure through a demand association algorithm; screening corresponding components from the reusable service component library through a service component matching mechanism; combining the screened components into a preliminary service template by using a service flow arrangement logic; optimizing the service template according to specific demand attributes in the dynamic demand map through a parameter self-adaptive adjuster to form a self-adaptive service assembly engine; the method comprises the following steps: deploying an adaptive service assembly engine into a cloud environment, and collecting actual use data through a service runtime monitor; and the actual use data is processed by the feedback analyzer to generate an optimization instruction. According to the invention, the public service platform can flexibly respond to demand changes, rapid deployment and continuous optimization of services are realized, and the intelligent level and service quality of the system are enhanced.

This invention relates to the fields of industrial automation control and smart water management, and discloses a multi-mode adaptive scheduling method for pump stations based on water volume prediction and dynamic optimization. The method includes: calculating the predicted water demand using an LSTM water volume prediction module combined with real-time meteorological characteristics; generating an optimal scheduling instruction set through a particle swarm optimization module with the goal of minimizing total system energy consumption; parsing the instructions and activating the corresponding control mode at the field control terminal, driving the pumps using a strategy combining feedforward compensation and PID control; and adaptively correcting the optimization model parameters using actual operating deviations using a closed-loop feedback analysis module. The system includes a water supply pump unit, a pipeline operation data sensing unit, a field control terminal, and an edge computing decision-making unit. This invention solves the problems of traditional control lag and model distortion, achieving global energy consumption optimization and high-precision stable control of the pump station.

The invention relates to the technical field of industrial wastewater treatment, in particular to a circulation coupling treatment system for a water treatment station in an industrial park, which comprises a reaction monitoring module, a dominant analysis module, a feedback analysis module and a feedback regulation module. Determining a sliding window of the corresponding monitoring data; constructing a ternary array as a processing path array, and calculating a dominant coefficient at any moment by using the change trend and amplitude level of data points in a sliding window corresponding to the monitoring data at any moment, so as to serve as a dominant coefficient of each processing path in the processing path array; and performing weighted fusion on all the dominant coefficients in the processing path array so as to determine a feedback coefficient at any moment, and adjusting the current density by using the feedback coefficient at the current moment. The treatment efficiency of the organic wastewater is improved.

An object of a system according to an embodiment is to improve the motivation of a learner and respond to individual learning needs.SOLUTION: A system according to an embodiment includes a quest generation unit, a persona generation unit, a feedback provision unit, and an emotion analysis unit. The quest generation unit analyzes the progress status of the learner and generates a quest to be challenged next. The persona generation unit analyzes the learner's profile or learning data based on the quest generated by the quest generation unit and generates an individual persona. The feedback providing unit visualizes the learner's performance based on the persona generated by the persona generation unit and provides feedback in real time. The emotion analysis unit analyzes the emotion of the learner based on the feedback provided by the feedback providing unit and adjusts the learning plan.SELECTED DRAWING: Figure 1

The invention discloses an edge calculation optimization method, system and device based on double-loop feedback iteration. The method comprises the following steps: firstly, setting a work target based on cross-scene task feature transfer learning through outer circulation, and decomposing the work target into work tasks to be distributed to an edge node group; secondly, working tasks are executed through internal circulation, and execution data are collected in real time; feedback analysis is carried out based on the execution data, deviation types are judged, and inner loop iteration or outer loop iteration is carried out; and finally, simulating an extreme working condition through an iteration effect mirror image evaluation mechanism, and correcting an iteration direction. According to the edge calculation optimization method based on the double-loop feedback iteration model, efficient and self-adaptive optimization of the edge calculation environment can be achieved, and safety, reliability and efficiency are improved.

This invention discloses a method and system for certificate generation and delivery in the field of big data processing, specifically for certificate-related business. The method includes the following steps: collecting original photos and user identification identifiers; generating processed ID photos, original photo hashes, processed ID photo hashes, cropped rectangle coordinates, and calculated photo specifications; binding the processed ID photos to the user identification identifiers; determining available cloud-based ID photos; generating certificate PDFs and associated data; collecting and correcting printed images; performing dual-benchmark verification and photo visual quality feedback analysis; generating dual-benchmark verification results and photo visual quality feedback results; and generating delivery instructions or rollback instructions. This invention achieves consistent photo specifications in PDFs and distinguishes and allows for targeted rollback of abnormal sources by establishing a cloud-based photo source traceability and dual-benchmark verification mechanism. It solves the problems of inherited, amplified, or incorrectly attributed photo generation deviations in existing technologies.

An object of a system according to an embodiment is to provide optimal education based on a learning history and interests of a child.SOLUTION: A system includes a collection part, an evaluation part, a provision part, a feedback analysis part, a support part, a progress management part, and a cooperation part. The collection unit collects data such as the child's learning history, test results, and interests. The evaluation unit evaluates the ability of the child on the basis of the data collected by the collection unit. The providing unit provides the individual curriculum based on a result evaluated by the evaluation unit. The feedback analysis unit analyzes the feedback of the child and the parent based on the curriculum provided by the providing unit. The support unit supports self-learning based on the feedback analyzed by the feedback analysis unit. The progress management unit manages the progress of the learning supported by the support unit. The cooperation part cooperates with the education service on the basis of the progress managed by the progress management part.SELECTED DRAWING: Figure 1

The application discloses a kind of electronic sand table personalized recommendation system in virtual construction system based on GraphRAG, it includes: data acquisition module: for collecting user behavior data, scene perception data and industry knowledge data;Data processing and analysis module: for analyzing user behavior data and scene identification and comparison;GraphRAG retrieval enhancement module: for knowledge graph construction, template and component library retrieval and enhance retrieval capability;Personalized recommendation module: for sand table template and sand table component recommendation;Personalized explanation generation module: using GraphRAG technology, for the template and component of recommended generation personalized explanation;Visual interactive module: including template, component interaction and dialogue interaction;Dynamic adjustment update module: for scene change identification and user feedback analysis.The application is realized scene perception and personalized recommendation by combining the behavior data of user and three-dimensional scene information, using industry knowledge graph, effectively improve the intelligent level of virtual construction.

The invention relates to a client pushing method and system for a vehicle-mounted system, and the method comprises the steps: obtaining vehicle machine data which comprises a vehicle position, environment data, power consumption, mileage and vehicle speed; a user logs in, and logged-in user information is obtained; transmitting the in-vehicle data and the user information to a server side, and calculating by using big data to obtain a user portrait; pushing an association service in real time based on the user portrait; and receiving feedback of the user to the push association service, and adjusting the push service based on user feedback data. According to the method, a multi-mode large language model is combined to upgrade a human-vehicle interaction mode, the interaction convenience and safety in the driving process are improved, a'recommendation-feedback-analysis' service data closed loop is formed by collecting user service feedback, user portraits are perfected, refined vehicle owner group operation is formed, and thus accurate vehicle owner recommendation service is provided.

Method (100) for executing a virtual manager and scheduler for scheduling activities for virtual machines (204), VMs, wherein the method comprises: Defining a schedule (102) for one or more activities to be performed on a virtual machine (204), wherein the schedule includes time information for the virtual machine (204) and wherein the time information includes active hours of the virtual machine (204) in the daily routine, active days of the virtual machine in the weekly routine, a time of maintenance activities, a time of deletion or shutdown, a time for a snapshot of the virtual machine, a backup time, a time to put the virtual machine (204) into sleep mode, or a time to resume the virtual machine; Applying (104) an adjustment to the schedule in accordance with feedback information received via a VM client (206); Summarizing (106) the feedback information from a plurality of VM clients (206) according to scheduled activity type, each VM client (206) belonging to a virtual machine; and Determine (108) a group fit for a determined group of VM clients (206) based on a function of the feedback information of the majority of VM clients (206).

The application discloses a seepage field cross-scale numerical simulation and feedback analysis method, comprising the following steps: S1, establishing a numerical calculation model for seepage field cross-scale analysis; S2, determining to be inverted seepage parameters and initialization, selecting observation points and constructing an objective function; S3, carrying out seepage cross-scale numerical calculation by using the numerical calculation model to obtain a simulation result of the seepage field; S4, calculating the value of the objective function and a Jacobian matrix according to the simulation result of the seepage field and observation information of an actual seepage field; S5, updating the to-be-inverted seepage parameters by using a Levenberg-Marquardt optimization method; and S6, outputting optimal estimation of the to-be-inverted seepage parameters and the seepage field calculation result when a convergence condition is met. Based on the method, the accuracy of the seepage field cross-scale numerical simulation and feedback analysis result is improved.

The invention discloses an intelligent electric pulse physiotherapy control method based on AI adaptive feedback, and relates to the field of electric pulse physiotherapy control, and the method comprises the following steps: collecting a biological feedback signal of a physiotherapy user, and collecting subjective feedback data of the user; converting the subjective feedback data into effective subjective data and preliminarily analyzing feedback analysis data between different biological feedback signals and the subjective feedback data; deeply analyzing the influence of different biological feedback signals on subjective feedback data, and constructing a historical reference analysis scheme and a prediction reference analysis scheme to carry out influence calibration on feedback analysis data to obtain feedback reference data; intelligent control is performed on the intelligent electric pulse physiotherapy based on the feedback reference data; the method and the device are used for solving the problem that the electric pulse intensity cannot be adjusted timely and accurately due to the fact that pain perception acquisition is not intelligent and not accurate enough in the existing electric pulse physiotherapy control technology.

The application discloses a deep learning-based adaptive prediction and ammonia injection flow field optimization method and system, and relates to the technical field of automatic ammonia injection. The deep learning-based adaptive prediction and ammonia injection flow field optimization method comprises the following steps: S1, collecting working condition data and emission monitoring data in the ammonia injection process, storing the data after preprocessing, and constructing an ammonia injection operation and maintenance database; S2, constructing an emission prediction model by adopting a recurrent neural network and a particle swarm optimization algorithm on training samples, performing precision evaluation on prediction errors, executing updating, and outputting prediction results; S3, performing ammonia injection optimization control analysis by using emission prediction data and ammonia escape amount; and S4, optimizing the ammonia injection strategy and adjusting the emission prediction model according to the correction feedback analysis result. The problems of the decrease of denitration efficiency, the non-standard emission and the serious ammonia escape phenomenon caused by the temperature and pressure parameter fluctuation in the combustion process are solved.