217 results about "Feedback analysis" patented technology

The invention discloses a large model prompt project optimization system and method fusing a domain knowledge graph. The system comprises an analysis module, a template generation engine module, a large model interaction interface module, a feedback analysis module and an optimization strategy module. And the analysis module forms a constraint coding signal containing an entity attribute incidence matrix. The template generation engine module forms an enhanced prompt text stream with a reservoir physical property parameter slot; the large model interaction interface module receives the enhanced prompt text stream and generates a question and answer response data stream containing geological terminologies; the feedback analysis module forms a feedback signal containing semantic deviation measurement through a semantic error vector calculation algorithm; and the optimization strategy module forms a parameter optimization instruction signal and transmits the parameter optimization instruction signal to the analysis module to complete iterative updating of the constraint condition. According to the large model prompt project optimization system fusing the domain knowledge graph, the problem of low answer accuracy of a large model in the oil-gas exploration field due to lack of professional constraints can be solved.

The invention provides a front-end automatic testing method of a large language model based on LLM, and belongs to the technical field of front-end automatic testing. The method comprises five core steps of test intention recognition and semantic analysis, page structure analysis and target element positioning, automatic generation of a test operation sequence and assertion logic, test script execution and dynamic regression verification, and test feedback analysis and continuous training. The strong semantic understanding and context reasoning capabilities of the LLM are utilized to perform semantic analysis and simulation on a front-end page structure, a user behavior process and business logic, so that automatic generation and maintenance of a test script are realized. According to the method, the test coverage rate and the generation efficiency are greatly improved, the maintenance cost is remarkably reduced, the readability and the intelligence of the test case are enhanced, and the method is suitable for the modern Web front-end application test of rapid iteration.

The invention discloses an online resource adaptive recommendation method based on multi-modal learning behavior analysis, and relates to the technical field of resource recommendation. The method comprises the following steps: firstly, dynamically collecting multi-modal data by using a heterogeneous sensor array, and carrying out noise reduction, probability distribution matching normalization and time-space alignment preprocessing; features are extracted through a hierarchical network, modeling learning behaviors such as a variational auto-encoder are combined, and the learning state is evaluated from multiple dimensions; recommendation decisions are generated based on reinforcement learning, recommendation is optimized in combination with personalized presentation and multi-source feedback analysis, meanwhile, the system has the functions of dynamic strategy adjustment, intelligent resource creation, cross-scene migration recommendation and the like, and accurate self-adaptive recommendation is achieved. According to the method, multi-modal data are comprehensively collected and deeply processed, learning behaviors and evaluation states are accurately analyzed, personalized resource recommendation is provided through intelligent recommendation and dynamic optimization strategies, recommendation accuracy and learning effects can be improved, user experience can be enhanced, and the utilization rate and competitiveness of platform resources can be improved.

The invention discloses an aquaculture intelligent feeding management system based on the Internet of Things, and relates to the technical field of aquaculture, a camera and a dissolved oxygen detector are utilized to construct an Internet of Things monitoring module, fish school behaviors and water quality environment data are collected in real time, and the movement track, group density and feeding state of a fish school are extracted; secondly, light-weight algorithms such as TinyYOLO and the like are adopted, rapid analysis of feeding intensity and feeding requirements is achieved in a local embedded computing module, a feeding model is generated, and dependence on high-performance hardware and cloud computing is reduced; meanwhile, the feeding control logic device dynamically calculates the optimal feeding amount and the optimal feeding opportunity based on the feeding state and the environmental characteristics; by monitoring the change of the ingestion intensity, the system catches the optimal ingestion window of the fish school, and maximization of the feed utilization rate is achieved; meanwhile, in combination with feedback analysis and a closed-loop optimization mechanism, model parameters are dynamically adjusted according to the feeding effect of the last round, and the environmental adaptability of the feeding plan is improved.

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 relates to the field of intelligent interactive design, and particularly discloses a visual intelligent interactive design system which comprises a three-dimensional structure design module, an intelligent color matching module, a visual rendering module and an interactive feedback analysis module. The three-dimensional structure design module can process imported or custom a three-dimensional model, detect and repair topology errors and construct a three-dimensional scene basic framework; the intelligent color matching module generates a color matching scheme based on the instruction, a rule base or user preference and displays a comparison view; the visual rendering module renders a three-dimensional scene in real time, collects rendering pipeline load parameters and quality indexes, and analyzes balance points to adjust rendering parameters; and the interaction feedback analysis module records interaction data, marks over-limit nodes by comparing a standard and analyzes a root cause. According to the system, efficient three-dimensional scene construction, intelligent color matching, rendering optimization and interaction experience improvement are realized through multi-module cooperation, and the system is suitable for multi-field scenes needing visual intelligent interaction design.

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 relates to the technical field of wastewater defluorination control, in particular to a wastewater defluorination control system suitable for a self-crystallization fluidized bed, which comprises a wastewater defluorination platform, an information acquisition unit, a defluorination state unit, a dosing supervision unit, a treatment matching unit, a tracking supervision unit and a management response unit, according to the method, analysis is carried out from two points of the target equipment and dosing, so that the defluorination efficiency of the target equipment is ensured, defluorination demand matching supervision analysis is carried out on the processing data in an information feedback mode, so that a defluorination scheme is reasonably matched according to the data processing condition, resource waste is avoided, the operation cost is reduced, and the method is suitable for popularization and application. Meanwhile, dosing control supervision feedback analysis is deeply carried out, on one hand, stirring interference of dosing is adjusted so as to ensure full contact reaction of fluorine ions in the wastewater, and on the other hand, the dosage is adjusted so as to ensure the fluorine removal efficiency of the wastewater and the rationality of automatic dosing control of chemicals.

The invention relates to the field of new-generation information technology and civil engineering, in particular to a frost heaving prevention technology of a roadbed in a seasonal frozen area, and particularly relates to a solar heating frost heaving prevention drainage roadbed in the seasonal frozen area and a construction method of the solar heating frost heaving prevention drainage roadbed. The method comprises the steps that environment sunlight data are obtained based on a solar heat collection device, heat energy is stored through an efficient heat storage material, and a heat energy output sequence is generated; acquiring soil temperature, humidity and frost heaving stress data from an environment sensor, predicting a frost heaving trend in combination with historical frost heaving characteristics, and generating regulation and control parameters; the heat energy output sequence and the frost heaving regulation and control parameters are input into a dynamic temperature control and drainage linkage module, heat distribution and optimization adjustment of a drainage path are carried out, and a linkage control strategy is generated; and performing feedback analysis on the operation condition of each module based on the data, and optimizing the control parameters of the dynamic temperature control and drainage linkage module. The temperature and humidity of the roadbed can be accurately adjusted, the frost heaving phenomenon is prevented, and roadbed drainage is optimized.

The invention relates to the field of intelligent management, and provides a numerical control machine tool post-market service item management method and management system, which mainly divides service item management into pre-sales management, in-sales management and after-sales management, in customer feedback management of the after-sales management, a data set fed back by a customer is extracted, and the customer feedback management of the after-sales management is completed. Semantic understanding of the customer feedback is carried out by adopting a data processing algorithm based on deep learning, so that whether the user satisfaction is positive or negative is automatically assessed according to significant dynamic aggregation representation of a distribution field domain between customer feedback semantic features; and it can be ensured that interpretation and classification of client feedback have higher objectivity and consistency. And moreover, nuisance in customer feedback can be captured, and customer emotion and potential problems behind can be perceived, so that more comprehensive feedback analysis can be provided.

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 relates to the technical field of virtual simulation and electrical engineering, in particular to an electrical simulation interaction method and system based on quantum prediction, and the method comprises the steps: generating holographic mapping data through loading three-dimensional simulation model data and electrical schematic diagram data, and carrying out the initialization; after capturing user interaction operation data, analyzing and generating optimized path data through a quantum heuristic prediction model, and adjusting the states of a model unit and an electrical primitive in real time; the simulation result data is used for state verification and feedback analysis, adjusting model parameters and optimizing path selection; fault-tolerant adjustment data is generated through virtual sandbox verification, a prediction model and holographic mapping data are updated, and self-learning optimization is achieved; according to the invention, the real-time performance, the response efficiency and the system adaptability of interaction are improved, and the method is suitable for demonstration and simulation of the electrical principle in education and engineering application.

The invention belongs to the field of communication transmission, relates to a data analysis technology, is used for solving the problems that time delay exists in channel state feedback and static weight cannot adapt to burst interference in the prior art, and particularly relates to an information communication method based on communication security protection, which comprises a link switching analysis sub-method and a feedback analysis sub-method. The link switching analysis sub-method comprises the following steps: acquiring channel parameters of a communication link and performing entropy conversion; carrying out weight distribution according to the entropy value of the channel parameter to obtain a weight coefficient of the sampling parameter in the acquisition period; analyzing the priority of the communication link; according to the method, the essential characteristics of the channel parameters can be dynamically captured, the timeliness and accuracy of the link switching decision are improved, the abnormal switching operation is effectively identified by a closed-loop feedback mechanism, the communication resource waste caused by invalid switching is reduced, and the method can maintain stable information transmission quality in a complex electromagnetic interference environment, so that the user experience is improved. And the communication interruption risk caused by channel abrupt change is avoided.

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 discloses a pumped storage power station underground powerhouse structure vibration test and excitation load feedback analysis method comprising the following steps: S1, combining time domain and frequency domain analysis to extract vibration characteristics of each structure of a powerhouse; s2, calculating three types of vibration sources, namely contribution degrees of machinery, hydraulic power and electricity to structural vibration; s3, adopting a finite element numerical simulation method and combining field actual measurement data to perform unit excitation load feedback analysis; the technical problems that the contribution of various vibration sources to plant vibration cannot be accurately judged in the prior art, so that the design of vibration control measures is lack of pertinence, and the transformation effect cannot be accurately predicted when the plant structure is subjected to anti-vibration optimization and transformation are solved.

The invention belongs to the technical field of numerical control machine tool manufacturing, and particularly relates to a five-axis machine tool spindle state dynamic monitoring method and system based on machining feedback. The method comprises the steps that key data in the machining process are collected in real time through multiple sensors installed on the five-axis machine tool; preprocessing the key data; performing processing feedback analysis according to the key data to obtain a processing feedback analysis result; performing spindle state evaluation according to the key data to obtain a spindle state evaluation result; and dynamically adjusting a monitoring strategy according to a processing feedback analysis result and a spindle state evaluation result. According to the method, key parameters in the machining process are monitored in real time, deep analysis and evaluation are carried out in combination with the machining characteristics of the five-axis machine tool, and therefore dynamic monitoring and accurate evaluation of the state of the main shaft are achieved, the monitoring accuracy and real-time performance are improved, various challenges possibly occurring in the complex machining environment of the five-axis machine tool are effectively coped with, and the machining efficiency of the five-axis machine tool is improved. And the safety and the stability of the machining process are ensured.

The invention belongs to the technical field of electronic teaching aids, and discloses a voice training system and a data training method after complete denture repair, and the system comprises a feedback analysis and decision device which is used for carrying out the error classification of a used object, and obtaining the type of a high-frequency problem through a clustering algorithm; the dynamic content generation engine is used for recording a historical error pattern of the use object, presetting pronunciation training logic and generating personalized training content; the intelligent difficulty adjusting device is used for adopting a dynamic difficulty algorithm: scoring according to a result of a use object, and automatically adjusting the level difficulty; and the adaptive content generator is used for analyzing the pronunciation content of the use object, identifying wrong phonemes or grammar problems, and generating training content according with difficulty in real time according to the current level and error type of the use object. The method can help a user to recover clear voice as soon as possible, improves the use enthusiasm, and can solve the problems that personalized training is not available, real-time monitoring and feedback cannot be performed, and pronunciation cannot be corrected in time.

The invention discloses an advertisement design project management system, which relates to the technical field of project management, and comprises an information acquisition unit, the information acquisition unit is used for acquiring operation information and feedback information and sending the operation information to an information analysis unit, and the information analysis unit acquires the operation information and extracts a browsing keyword set based on the operation information; the method comprises the following steps: respectively calculating comprehensive demand indexes of browsing keywords and dividing pushing grades of the keywords, acquiring user information by an advertisement distribution unit, carrying out association matching on the user information and a coincident keyword set, and pushing associated keywords to a matched pushing user set, acquiring feedback information by a feedback analysis unit, calculating a comprehensive feedback coefficient, and sending the comprehensive feedback coefficient to the advertisement distribution unit. And a putting adjustment signal is generated. According to the method, by dividing the pushing levels of the keywords, the advertisement pushing accuracy is improved, the project management efficiency is improved, the advertisement putting effect is optimized in real time through feedback adjustment, the advertisement cost can be effectively reduced, and the rate of return on investment is improved.

The invention relates to the technical field of electrical fire identification, in particular to an electrical fire intelligent identification method and system based on a visual image, and the system comprises a visual image fire identification platform, a fire information base, an infrared image analysis unit, a region identification unit, a feature matching unit, a dynamic management and control unit and an alarm response unit. According to the method, regional fire monitoring feedback analysis is performed on the infrared feature image preliminarily, so that the suspicious risk condition of each monitoring point in the target electrical equipment can be known, and data support is provided for subsequent analysis; whether the target electrical equipment has a fire or not is analyzed from the two aspects of infrared feature image processing and monitoring video image feature extraction, and through the mode of combining the two fire analysis methods, the fire recognition error rate is reduced, the target electrical equipment with a disaster is analyzed deeply, and the fire recognition efficiency is improved. Reasonable management and control can be carried out according to the dynamic change trend of the fire, and the fire management efficiency can be 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 big data processing and intelligent optimization, in particular to a rural space optimization method and system, and the method comprises the steps: collecting multi-dimensional data in a rural region in real time, carrying out the dynamic feedback analysis through an AI-driven feedback system, and combining a multi-agent system with a game theory model, thereby generating an optimal space layout path. And then, through association rule mining and a dynamic target re-optimization algorithm, continuously adjusting and optimizing the rural space layout, and realizing a long-acting optimization mechanism. According to the invention, changes can be responded in real time in a dynamic environment, sustainable development of a rural area is ensured, ecological protection, economic benefits and social acceptance are improved, and comprehensive optimization of a rural space is realized.

The invention discloses a personalized teaching skill training system based on a large language model, equipment, a medium and a product, and relates to the technical field of teaching skill training.In the system, firstly, a teaching skill learning module provides answers meeting teaching requirements for teaching questions proposed by teachers so as to help the teachers to learn teaching skills; secondly, a plurality of virtual student roles and live-action teaching scenes are generated through a live-action teaching simulation module, and the virtual student roles and the live-action teaching scenes are simulated by teachers in an online video mode, so that the actual teaching ability is trained and improved; the teaching feedback analysis module analyzes the teaching behavior performance data and the teacher-student interaction data, generates a report and provides suggestions for defects; and finally, proper teaching skill training resources are recommended through a teaching resource recommendation module, so that the teacher is helped to deeply learn and improve the teaching method. According to the scheme of the invention, the teaching ability of teachers can be effectively improved, and especially the coping ability of the teachers facing diversified student behaviors and demands can be effectively improved.

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 charger charging current control system and method based on feedback analysis, and relates to the technical field of chargers, and the method comprises the steps: carrying out the real-time collection of key charging behavior parameters, such as connection time, voltage waveform, steady-state building time, and the like through a plurality of built-in modules, such as a USB / PD handshake monitor, an ADC sampling module, and a current sampler; data cleaning and standardization are carried out in the central processing unit, and a behavior stability scoring function Wdev for representing the stability of the plugging behavior of the user is constructed. And comparing the function with a behavior stability threshold value Wth to judge whether the current charging state is an unstable charging state or not. Compared with the traditional technology only based on single current and voltage signal current limiting, the scheme has higher behavior identification capability and preposed decision-making capability, and can perform stability modeling and risk pre-judgment on the charging behavior of the user on the premise of not changing the hardware structure.

The invention discloses a warpage marking device, and relates to the technical field of glass substrate warpage detection, the warpage marking device comprises a detection equipment main body, the middle position of the detection equipment main body is fixedly connected with a detection table, a driving pneumatic cylinder is installed above the detection table, and the output shaft end of the driving pneumatic cylinder is provided with a detector; the detector is located at the eccentric position above the substrate main body, so that detection is not limited to the central area of the plate, the surface of the substrate main body can be completely covered, more accurate surface data feedback analysis is achieved, the surface integrity of the substrate main body can be evaluated more accurately, and meanwhile the detection accuracy is improved through dynamic adjustment of the detection area in the process. Different detection positions of the detector are increased while the irradiation range of the detector is reduced, so that each part of the substrate can be subjected to uniform and sufficient detection feedback, the problem that in a traditional method, light is excessively focused on a central area and detection of an edge area is insufficient is solved, and uniform distribution and comprehensive coverage of detection light are ensured.

The invention relates to a stateful protocol fuzzy test method and system based on response information. The method comprises the following steps: S1, a fuzzy test preprocessing stage; s2, a basic state identification stage; s3, a double-layer state subdivision stage; s4, a state evaluation and selection stage; s5, a fuzzy test execution stage; and S6, a feedback analysis stage. The system comprises a state division module, a state evaluation module, a test execution module and a feedback analysis module. According to the method, the efficiency and the accuracy of protocol fuzz testing are remarkably improved through a double-layer state recognition and dynamic evaluation mechanism. In the aspect of state recognition, a basic state identifier is firstly constructed based on the combination of a response code and a control field, and then state subdivision is realized through path feature analysis, so that state confusion and redundancy are effectively avoided. In the aspect of state evaluation, the key test of the key control node is realized by analyzing the topological characteristics, the historical income and the transition probability of the node.

The invention relates to the technical field of greenhouse planting management, in particular to a visual detection method for crops planted in an agricultural greenhouse. On the premise that image processing reaches the standard, image growth state recognition feedback analysis is carried out on the analysis image to know the growth state of each planted crop, reasonable management is carried out through feedback information to improve the growth health of the planted crops, regional planting disease hazard recognition evaluation analysis is carried out in a progressive mode, and the management efficiency is improved. According to the method, the disease details of the planted crops are managed in a targeted manner, local treatment or overall treatment is performed on the target area, the growth risk of the planted crops in the target area is reduced, and normal growth health risk assessment management analysis based on the planted crops is analyzed. Therefore, the growth health condition of each planted crop can be intuitively known, the planted crops can be reasonably and specifically managed, and the growth health of the planted crops can be improved.

The invention relates to the technical field of data feedback control, and discloses a pregnancy health care control system based on data feedback analysis, which comprises a data acquisition module, a dynamic physiological feature mapping module, an implicit feedback channel module, a self-stabilization control module and a care execution module. By constructing the dynamic physiological feature mapping matrix, the multi-dimensional physiological data and the historical trend of the pregnant woman are deeply fused, the continuous health state vector is generated, and the limitation that in the prior art, a single threshold value is relied on, and dynamic adaptive capacity is lacked is broken through. Meanwhile, an implicit feedback and self-stabilization control mechanism is introduced into the system, the nursing strategy can be automatically adjusted when data abnormity or environment change is detected, pregnancy health management with individualized, continuous and robust coexistence is achieved, and the sensitivity, the stability and the individualized nursing capacity of the monitoring system are remarkably improved.