112 results about "Feedback analysis" patented technology

The invention relates to the technical field of artificial intelligence, and discloses a professional knowledge question and answer intelligent customer service system based on a self-optimization mechanism. The system comprises a user intention analysis module, a knowledge processing module, a self-optimization learning module and an interactive presentation module. A semantic understanding unit of the user intention analysis module generates a user intention signal; after the knowledge processing module receives the signal, a knowledge retrieval unit outputs related knowledge fragments and confidence, an answer generation unit forms candidate answers, and a quality evaluation unit determines an optimal answer according to the confidence; in the self-optimization learning module, a feedback analysis unit adjusts answer generation parameters according to user interaction data, a strategy adjustment unit optimizes a retrieval strategy in combination with an optimal answer and a historical dialogue, and a knowledge updating unit updates a knowledge base depending on an external knowledge source; and a multi-round dialogue management unit of the interactive presentation module adjusts a dialogue process, and a visual presentation unit outputs a natural language text and collects user feedback to a feedback analysis unit.

The invention discloses a consumer feedback analysis method based on a multi-agent model, and the method comprises the steps: firstly sampling and generating consumer multi-dimensional feature data, and expanding the data into a semantic portrait through a large model; therefore, an intelligent agent containing a memory module is constructed, and part of the intelligent agent is set as an opinion leader. Commodity attributes, propaganda and competitive products are input into each agent, and initial evaluation is independently output; and then multiple rounds of viewpoint interaction are carried out in the same social evaluation area, the opinion leader has a higher sampled weight, and memory and comments are updated. And after simulation is finished, updating evaluation is generated again and compared with the initial evaluation, attitude changes are analyzed, all data are summarized, and a visual comprehensive report is output. According to the method, accurate simulation and feedback analysis of consumer behaviors are realized by combining a large language model and a multi-agent simulation test technology, and the defects of a traditional method in the aspects of consumer portrait dynamics, agent adaptability, interaction complexity, data dependence and the like are overcome.

The invention discloses an intelligent verification system and method for full-process review based on multi-modal analysis, and belongs to the technical field of intelligent review. Comprising a processing analysis module, an experiment extraction module, a risk early warning module, a reproduction verification module, a chart comparison module, a dispute tracing module, a feedback analysis module, a load monitoring module, a report generation module and a preference analysis module. According to the invention, comprehensive and multi-angle intelligent review can be realized, more detailed risk early warning and positioning information can be generated, the experiment reproducibility can be quickly verified at low cost, the manual verification burden is greatly reduced, the innovation and risk of the thesis viewpoint are scientifically evaluated, the fatigue of a manuscript reviewer is relieved, the manuscript review efficiency and quality are improved, and the method is suitable for popularization and application. And dynamically adjusting the review content recommendation sequence.

The invention discloses an industrial control protocol intelligent fuzzy test method and system based on a multi-agent large model, and relates to an industrial information security test method and system.According to the industrial control protocol intelligent fuzzy test method and system based on the multi-agent large model, the large model is enhanced by integrating the field of the retrieval enhancement generation (RAG) and the low-rank quantization adaptation (QLoRA) technology, and a multi-agent cooperation mechanism is combined; and full-automatic, high-precision and end-to-end fuzzy testing of the industrial protocol is realized. The system generates seed data meeting protocol specifications through the seed generation agent, the test case generation agent executes field, structure and semantic variation based on the seed data, efficient test cases are dynamically generated, a test strategy is optimized in real time through the feedback analysis and strategy adjustment agent, and the vulnerability discovery capability is improved. By dynamically adjusting the variation strategy and optimizing the generation of the test case, the coverage, the accuracy and the efficiency of the test are improved, and the security and the vulnerability detection capability of the industrial control system are remarkably improved.

The invention provides a hybrid AI adaptive optimization system based on agent context engineering. The hybrid AI adaptive optimization system comprises a context knowledge base, a generation module, a feedback analysis module and a knowledge integration module. According to the method, the problems that in an existing context optimization technology based on a large language model (LLM), context Bias is simplified, Context Collapse is caused by overall rewriting, and the learning process is high in delay, high in cost, unstable and the like are solved.

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 discloses a thoracic surgery patient postoperative remote monitoring method and system based on the Internet of Things, and relates to the technical field of medical rehabilitation monitoring. Feature index extraction is carried out by taking body position pressure and respiration collaborative response as a two-factor dynamic evaluation basis, so that high-sensitivity judgment on a thoracic cavity load state is formed; after the abnormal state is recognized, body position adjustment is carried out, acoustic feedback analysis is linked, secondary evaluation after body position adjustment is achieved, intervention effectiveness of body position adjustment is ensured, personalized adjustment suggestions are automatically generated, the whole process of'perception-recognition-execution 'of remote monitoring is opened, the intelligent level and response real-time performance of postoperative recovery management are improved, and the postoperative recovery management efficiency is improved. According to the overall scheme, health risks caused by position misjudgment, intervention lag and monitoring blind areas in a traditional system are effectively avoided.

The invention discloses a model robustness automatic evaluation method based on large model driving and related equipment. The method comprises the following steps: inputting a task template of a tested model into a dynamic Prompt engine module to obtain a sample generation instruction; generating an adversarial sample according to the sample generation instruction through a sample generation and verification module, and performing model evaluation on the adversarial sample; if the confrontation sample passes the model verification, extracting a high-dimensional multi-modal feedback vector of the tested model through a multi-modal feedback analysis module; a reusable semantic instruction is generated through a strategy control module according to the high-dimensional multi-modal feedback vector so as to optimize a generation strategy; and if the confrontation sample does not pass the model verification, performing effect evaluation on the confrontation sample through an evaluation and interpretation generation module and generating an interpretability evaluation report. According to the method, progressive generation of the adversarial sample and exponential-level improvement of the model robustness evaluation efficiency can be realized, a clear model improvement direction is provided for developers, and the method can be widely applied to the technical field of computers.

The invention discloses a knowledge base construction and learning feedback analysis method and device for a data structure course, equipment and a storage medium, relates to the technical field of course analysis, and discloses a knowledge base construction and learning feedback analysis method for a data structure course, which comprises the following steps: acquiring multi-source data associated with the data structure course, and identifying the multi-source data to obtain a learning feedback analysis result; obtaining structured data; identifying the structured data, generating an entity set, associating entities with course targets, and generating knowledge point course target mapping; the entities are fused according to the character string similarity and the semantic similarity, and a dynamic knowledge base is generated; searching a dynamic knowledge base according to the question content, generating a question answer according to the associated triple, and determining answer feedback according to the question answer; and according to the answer feedback, calculating a course goal achievement degree, according to the course goal achievement degree and knowledge point-course goal mapping, generating a teaching adjustment suggestion, and completing data structure course knowledge base construction and learning feedback analysis.

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.

Systems, devices, and methods for delivering laser energy directed toward target tissue using a spectroscopic feedback. An exemplary laser feedback control system comprises a feedback analyzer to receive a signal from a target tissue using a spectroscopic sensor, and a laser controller to determine whether the received signal generally equals a first preset. If the received signal meets the first preset, the laser controller can send a control signal to a laser system to change from a first state to a second state of the first laser system. The laser system can deliver laser energy via an optical fiber towards the target tissue.

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.

The present application relates to the technical field of medical information analysis, in particular to a IBS-D symptom dynamic monitoring and doctor-patient interaction terminal, the present application extracts first characteristic medical information and second characteristic medical information through an irritable bowel feedback analysis model, and the second characteristic medical information is calibrated and quantified to obtain third characteristic medical information under the condition of containing the first characteristic medical information; the first characteristic medical information and the third characteristic medical information are combined as key quantitative information to generate an IBS-D medical monitoring feature report; through the method, the physiological information and the communication information of the monitored IBS-D patient can be quantified, and a medical monitoring feature report is generated based on the information, so as to expand the application range of the monitoring data to the treatment data, reduce the communication information error caused by the disease of the patient, and provide accurate data for the doctor to make data reference.

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.

The invention relates to the technical field of digital human image generation, in particular to a digital human image generation system for personalized feature modeling, which comprises a dynamic feature modeling subsystem, an intelligent configuration feedback subsystem, an interactive friendly configuration subsystem and a data storage module, the dynamic feature modeling subsystem acquires new feature data of a user in real time through a dynamic data acquisition unit, dynamic updating of model parameters is realized in combination with an incremental feature learning unit, the intelligent configuration feedback subsystem constructs a'data acquisition-feedback analysis-strategy adjustment 'closed loop, and a configuration strategy is optimized based on reinforcement learning. The interactive friendly configuration subsystem improves operation convenience through intelligent template recommendation, real-time preview rendering and multi-dimensional linkage configuration, dynamic adaptation of digital human feature modeling, real-time optimization of a configuration strategy and high efficiency and friendliness of user interaction are realized, and personalized service capability and user experience are remarkably 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.