116 results about "Process evaluation" patented technology

The invention discloses a computer interactive programming platform automatic evaluation system based on deep learning, and particularly relates to the technical field of deep learning, the system comprises five modules, namely a structure diagram construction module, a semantic diagram generation module, a dynamic evaluation trigger module, a semantic solution identification module and an exponential deduction feedback module, and full-process evaluation from code structure abstraction to semantic modeling is realized. The system dynamically controls a deep evaluation process through a structure matching rate and a logic deviation degree, identifies a potential innovation solution, generates a semantic equivalence degree and a path innovation index, outputs a grade in combination with a neural network score, and embeds a high-innovation sample into a training buffer area to update a model, so as to realize intelligent evaluation and adaptive optimization; according to the method, the modeling precision of a program structure and a control flow is improved, dynamic regulation and control of semantic understanding and an evaluation process are realized, a potential innovation solution can be identified, and model self-updating is realized through scoring grade feedback, so that the intelligent analysis and adaptive evolution capability of an evaluation system on complex programming behaviors is enhanced.

The invention discloses an electromechanical industry digital process evaluation method based on data analysis, and particularly relates to the technical field of digital evaluation, a behavior path map, a time sequence causal dependence model and an operation frequency density model are constructed based on information provided by the electromechanical industry, whether structural deviation or behavior abnormity exists is analyzed, and the evaluation result is obtained. If the initial deviation label is generated, calculating a behavior consistency score and a process integrity score, inputting the scores into a fuzzy logic device for risk reasoning, and outputting a credible level; according to the credibility level, judging whether the data is suitable for digital process evaluation, and if the data does not meet the preset requirement, feeding back a corresponding optimization strategy; according to the method, digital behavior structured analysis is realized by constructing a behavior path map, a time sequence causal dependence model and an operation frequency density model; a deviation triggering mechanism is set, and abnormal operation behaviors are accurately recognized; the credibility level is output based on the scoring result, the information applicability is judged according to the credibility level, an optimization strategy is fed back, and the evaluation intelligence level is improved.

A system for evaluating a pull request process for a code repository is configured to access pull request data for a plurality of completed pull requests associated with code stored in a code repository and process the pull request data to identify pull requests with a policy pass / fail characteristic indicative of environmental error. The identified pull requests are then analyzed to determine which infrastructure and / or software component of a code review system is a source of the environmental error and / or a rate of occurrence of the policy pass / fail characteristic in the completed pull requests. An alert is then generated via a user interface of the pull request process evaluation system indicating an environmental error to indicate which infrastructure and / or software component of the code review system is a source of the environmental error and / or the rate of occurrence of the policy pass / fail characteristic in the completed pull requests.

The invention relates to the field of education data mining and teaching process evaluation, in particular to an online and offline mixed teaching performance dynamic evaluation method and system based on a PDCA (Packet Data Convergence Architecture) circulation, and the method comprises the steps: generating initial Rubric configuration and formulating a multi-source data collection scheme through the analysis of course types and learning condition information around the PDCA circulation; then, online and offline multi-modal information is collected and preprocessed, and data with labels and basic statistics are obtained; and in combination with causal graph construction and quantum multi-group fuzzy weight optimization, carrying out comprehensive evaluation on the data, outputting adaptive Rubric configuration and student scores, and generating a readable report and an early warning through a neural fuzzy abstract. And according to the score and early warning, implementing difference enhancement and holographic AR feedback, collecting intervention process data again, and dynamically adjusting Rubric to complete iteration. According to the invention, the teaching performance can be continuously optimized, and accurate early warning and personalized intervention are realized.

The invention relates to the technical field of software development training, in particular to a software development post pre-post training method based on intelligent analysis, and the method comprises the following steps: S1, evaluating and constructing a multi-dimensional capability digital portrait baseline; s2, skill book modeling driven by the knowledge graph; s3, an adaptive course generation engine; s4, constructing an intelligent practical training environment; s5, establishing a process evaluation index system; and S6, path tuning dynamic feedback is carried out. Through the intelligent analysis system, intelligent evaluation and student digital ability portrait construction are carried out, personalized learning path planning, intelligent teaching resource matching, dynamic course generation and a dynamic evaluation feedback system are fused, precise evaluation and adaptive optimization of the training process are realized, and the training effect is obviously better than that of a traditional training mode. Post talents suitable for software development are efficiently trained through intelligent dynamic ability evaluation and immersive training, and if personnel not suitable for software development are intelligently evaluated by the system, the personnel can be automatically evaluated to other suitable posts.

The invention relates to a discrete manufacturing process evaluation method based on deep learning. Comprising an equipment performance data acquisition module for collecting key performance index data of various processing equipment; the equipment performance evaluation module adopts a weighted index combination and hierarchical evaluation mechanism, introduces a real-time state sensing mechanism, and evaluates the equipment performance in a multi-dimensional and multi-level manner; the process intelligent analysis module fuses historical process data and equipment performance data, constructs deep learning model input through feature extraction, and realizes identification of key difficulties of the processing process and prediction of the process success rate; and the process feasibility evaluation module combines the trained deep learning model with the equipment performance evaluation result to form the process feasibility automatic evaluation method for specific equipment and workpieces. According to the method, intelligent decision-making of equipment type selection and a process path in a manufacturing process can be realized, an enterprise is helped to realize optimization of production efficiency and product quality, and the production efficiency and the product quality of a manufacturing system are comprehensively improved.

The invention discloses a model-based sewage treatment plant data quality control and process evaluation analysis method and system, and belongs to the technical field of sewage treatment. The method aims at solving the problems that a current sewage treatment plant data acquisition system faces data missing, abnormity and deviation, and data quality control and process evaluation are separated from each other, the intelligent degree is low, and the adaptability is poor in the prior art. The method comprises the following steps: firstly, comprehensively evaluating original data by using a data quality evaluation model, and accurately identifying and processing various problem data; a complex association relationship among process parameters is deeply mined through a process association analysis model, and a whole-flow process knowledge graph is constructed; and finally, in combination with a data quality evaluation result and the process knowledge graph, realizing accurate evaluation and optimization adjustment of the process operation state. The data quality management and control level of the sewage treatment plant is effectively improved, the accuracy of process evaluation is enhanced, powerful support is provided for stable operation and efficient management of the sewage treatment plant, and the sewage treatment industry is promoted to develop towards the intelligent and refined direction.

The invention discloses a multi-dimensional comprehensive evaluation method for permeability resistance of overlying strata of a working face, and belongs to the technical field of mine engineering and geological safety evaluation. 12 types of core factors such as rock strength, rock core quality, physical and mechanical properties of rock mass, hydrological properties and mining influence characteristics are integrated; a full-process evaluation framework of data acquisition, index system construction, weight distribution, comprehensive modeling and verification optimization is constructed, an analytic hierarchy process and an entropy evaluation method are coupled to determine index weights, a dynamic evaluation model is constructed in combination with a fuzzy mathematics theory, and accurate classification and risk early warning of the permeability resistance of the overlying strata are realized. According to the method, through comprehensive analysis of a plurality of factors, the accuracy of overlying strata permeability resistance evaluation can be improved, so that the underground water permeation path and the permeation amount are predicted more accurately, the uncertainty is reduced, the comprehensiveness and the accuracy of evaluation are remarkably improved, and a scientific basis can be provided for mine water disaster prevention and control and safe mining.

The invention discloses a carbon anode calcination process monitoring system based on Internet of Things, and particularly relates to the field of calcination process monitoring, comprising a region division module, a data acquisition module, a process parameter analysis module, an overall process evaluation module, an abnormality judgment module and an interactive feedback module. According to the invention, through the Internet of Things sensor, comprehensive real-time monitoring of the carbon anode calcination process is realized. The regional division module subdivides calcining equipment, and the data acquisition module can obtain rich parameter information, covers multiple aspects such as process, equipment and environment, and provides powerful support for accurately mastering the process state; according to the invention, the mathematical model is constructed through the process parameter analysis module and the overall process evaluation module, and the collected data is comprehensively analyzed, so that the stability of the process, the product quality influence factors and the overall risk condition can be accurately reflected, which is helpful for the management personnel to deeply understand the process and improve the quality and production efficiency of the carbon anode.

The invention discloses an intelligent interaction process evaluation system based on multi-dimensional dynamic data, and relates to the technical field of process evaluation, a dynamic representative election module is constructed, and library representatives are selected based on feature vectors and qualification scores by calculating the feature vectors of dynamic data in a plurality of sub-databases in real time; constructing an event driving module, collecting time sequence event streams in a data bus in a preset period, and setting the time sequence event streams as an event group; constructing a job allocation module, and allocating an independent job group to each event in the event group based on the event group and the library representative; constructing an evaluation center, reporting events through an independent job group, generating independent evaluation results by voting, generating a plurality of evaluation results by a plurality of events, and selectively outputting the evaluation results based on evaluation requirements; through the dynamic representative election module and the role interaction and counterbalance type evaluation structure, the timeliness and pertinence of the evaluation result and the adaptability to the dynamic environment are remarkably improved.

The invention relates to a collaborative learning process evaluation and intervention system and method, and belongs to the technical field of artificial intelligence. The method comprises the following steps: acquiring multi-modal original data from an online collaboration environment in real time through a data acquisition module, performing timestamp synchronization, preprocessing and packaging, and generating a standardized synchronization event stream; a dynamic multilayer heterogeneous interaction graph is constructed or updated in real time based on the event flow through a graph construction module, wherein the graph comprises student nodes, concept nodes and workpiece nodes; carrying out snapshot analysis on the atlas through an analysis engine in a preset time window, and calculating and outputting a multi-dimensional social measurement index reflecting a collaboration process state; and continuously monitoring the index time sequence through an AI tutor intervention module, and when a predefined cooperation mode is detected, triggering a decision-making mechanism to generate an intervention action and feeding the intervention action back to the online cooperation environment. Therefore, real-time, objective and multi-modal evaluation of the collaborative learning process is realized, and accurate and timely intervention is carried out, so that the quality and effect of collaborative learning are improved.

The embodiment of the invention discloses a process evaluation system and method, electronic equipment and a computer readable storage medium, the system comprises a data acquisition module, an index determination module and an evaluation analysis module, operation data generated in the process of process operation is acquired through the data acquisition module, the index determination module analyzes the operation data, and the evaluation analysis module analyzes the operation data; according to the method, index parameters including aging parameters, abnormal parameters, rejected parameters and / or design defect parameters are determined, an evaluation analysis module performs health degree evaluation on the process according to the index parameters, an evaluation result is determined, and the process health degree can be evaluated more comprehensively and systematically.

The invention provides a fine tuning method of a preset model, and a question answering method and device based on the preset model, and relates to the technical field of artificial intelligence. The fine tuning method comprises the following steps: rewriting a sample problem by utilizing a preset model to obtain a retrieval problem; performing retrieval based on the retrieval problem to obtain a retrieval result for the retrieval problem; performing reflection on the retrieval result by utilizing a preset model to obtain a reflection result aiming at the retrieval result; under the condition that the reflection result represents that the retrieval result meets a preset answer generation condition, generating an answer of the sample question based on the retrieval result by utilizing a preset model; respectively evaluating the retrieval result and the answer to obtain a process evaluation score for the retrieval result and a result evaluation score for the answer; and performing fine tuning on parameters of a preset model based on a training sample constructed from the sample question, the answer, the retrieval result, the process evaluation score and the result evaluation score.

The invention relates to the technical field of engineering machinery production lines, and mainly relates to a simulation-based engineering machinery structural part production line bottleneck optimization method and device and a medium. The identification and judgment method for the bottleneck process of the production line specifically comprises the six steps of determining production line logistics simulation evaluation indexes, defining the priority of the production line logistics evaluation indexes, constructing a production line digital simulation model, outputting a production line simulation result, determining bottleneck stations of the production line, achieving optimization through simulation optimization and the like. According to the method, a production line simulation model is established based on a digital factory simulation platform, the operation performance of each station device of the production line can be quantitatively evaluated through simulation output data and quantitative bottleneck process evaluation indexes, the bottleneck process of the production line is effectively verified, and investment and research and development risks are reduced.

The invention discloses an auxiliary evaluation system for future scene guidance. The auxiliary evaluation system comprises an evaluation management module, an evaluation control module and an evaluation process module, the evaluation management module is used for defining an evaluation stage, an evaluation standard and a risk probability calculation method; the method comprises the following execution steps: defining an evaluated session scene, evaluation content and an evaluation stage; determining an evaluation standard and a scoring dimension, and determining a method for calculating a risk probability according to the evaluation standard; setting an evaluation plan according to the risk probability; the evaluation control module is used for executing the evaluation plan and initiating an evaluation event to the evaluation process module; the evaluation process module is used for responding to the evaluation event, providing evaluation content for the user side according to the evaluation stage, calculating the risk probability of the evaluation stage according to the feedback result of the user side, and generating an evaluation result and an evaluation plan. According to the technical scheme, assessment obstacles caused by high frequency and multi-mode characteristics in the future scene guidance psychological assessment process can be effectively solved, and the assessment process is dynamic and procedural.

1. The name of the design product: graphical user interface for dance course process evaluation. 2. The use of the design product: an electronic device containing a graphical user interface for dance course process evaluation. 3. The design points of the design product: the content of the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: the interface of the design product is a graphical user interface that can be used for dance course process evaluation, and the interface of the front view is a login interface. After logging in, the dance course process evaluation system can be used in the graphical user interface. 6. The human-computer interaction mode of the graphical user interface: the front view after login gets the interface change state diagram.

This invention provides a method, system, equipment, and medium for evaluating the execution progress of distribution network projects, relating to the field of distribution network management technology. The method includes: acquiring operational data of the distribution network for the current time period and node information for each execution node; the operational data includes source-load data for conventional equipment and renewable energy equipment; based on this data, constructing a multi-dimensional vector and calculating the initial progress score for each execution node; extracting features from the source-load data to generate a source-load trend-fluctuation hierarchical representation, and determining the source-load coupling scenario category and fluctuation weight through dual-channel feature extraction; combining the scenario category and node information to determine the dynamic sensitivity coefficient and dynamic correction coefficient for each node; performing asymmetric correction on the initial progress score based on the dynamic correction coefficient to obtain the final progress score, and integrating the scores of all nodes to obtain the execution progress evaluation result for the corresponding distribution network project. This invention improves the accuracy and reliability of distribution network project execution progress evaluation.

The application discloses a kind of based on multi-source data fusion and process evaluation's college student comprehensive performance automatic generation method and system, including S1 establishes ideological and political evaluation model, academic performance evaluation model, practical ability evaluation model, comprehensive quality evaluation model, development potential evaluation model comment model. S2 by middleware establishes standardization interface and automatically reads the heterogeneous data source data of educational administration system, school system, campus card system, library system, scientific research and teaching research practical training system, second classroom activity platform etc.S3 to behavior sequence is carried out pattern recognition and feature extraction, establishes student panoramic data warehouse, and the data of step S2 is labeled with S1 evaluation model label and storage.S4 user selects comment purpose.S5 dynamic weight distribution.S6 to student data is screened.S7 comment automatic generation.S8 artificial check comment.S9 generation visual report.The application improves work efficiency, and can provide accurate student performance in school for parents and employing units.

The application discloses a method and system for identifying abnormalities in the coagulation process based on big data analysis, comprising: combining standard coagulation detection and thromboelastography dynamic monitoring to realize the leap from static indicators to functional whole-process evaluation, while combining patient individual characteristics to screen similar historical cases, and accurately identifying key coagulation indicators; introducing correlation analysis to dynamically screen key indicators, and using clustering analysis to establish an adaptive normal range, and finally evaluating abnormalities by quantifying the degree of deviation, the application significantly improves the accuracy and timeliness of coagulation state monitoring, provides individualized early warning and intervention basis for clinical practice, effectively prevents bleeding or thrombosis risk, and promotes the intelligent and refined development of coagulation management.

The invention provides a method for determining the form of a silver mineral, and belongs to the technical field of process mineralogy. The method comprises the following steps of silver ore sample preparation, first-time automatic mineralogy analysis, layer-by-layer stripping and repeated analysis, substance composition measurement and coefficient calculation, comprehensive morphological parameter calculation and morphological statistics. According to the method, through a strategy of combining'surface layer-by-layer analysis-three-dimensional parameter reconstruction 'and'process product analysis-distribution behavior analysis', accurate quantification of two-dimensional / three-dimensional forms (such as length-width ratio, thickness and complexity) of the silver minerals is realized, and the process mineralogy characteristics of different types of silver minerals are disclosed synchronously; comprehensive and accurate data support is provided for silver ore crushing particle size optimization, sorting process selection and process evaluation, and the defects that a traditional method is single in form information and insufficient in correlation with process behaviors are overcome.

The invention discloses a clinical medicine practice skill evaluation standard formulating system, and relates to the technical field of medical education evaluation, and the system comprises a system resource and authority presetting module, an evaluation content construction module, a user role responsibility clarification module, a multi-scene evaluation execution and data processing module, and an evaluation system dynamic optimization and sharing module. According to the method, on the basis of a clinical ability framework of a medical examination institution, examination outline requirements of clinical practitioners are integrated, clinical thinking and humanistic care dimensions are supplemented, a four-class eight-dimensional process evaluation mode is innovatively constructed, the problems that in traditional evaluation, the result is heavy, the process is light, and the evaluation dimension is single are solved, and the evaluation efficiency is improved. The four classes cover the learning and practice links of students, the eight dimensions further refine the specific evaluation indexes, and then are in butt joint with clinical skill training center equipment, multiple classes of teaching tools are integrated, and hardware and software support is provided for landing of four-class eight-dimension evaluation; the data of each dimension is obtained in real time in the scene inside and outside the school, and the comprehensive evaluation result is generated.

The application relates to the technical field of medical artificial intelligence, and discloses a large language model medical numerical reasoning ability process evaluation method and system. The method comprises the following steps: obtaining a structured abstract of medical research literature; inputting the structured abstract into a large language model to be evaluated, performing binary judgment on each candidate conclusion, and outputting a correct candidate conclusion set supported by numerical evidence and context information and a reasoning text; determining the correctness of the large language model at the answer level; aligning the reasoning text with a preset structured standard explanation item by item to evaluate the reasoning process of the large language model; and comprehensively evaluating the correctness at the answer level and the evaluation result of the reasoning process to output a comprehensive ability evaluation of the large language model in a medical numerical reasoning task. The application can systematically, finely and interpretively evaluate the comprehensive numerical reasoning ability of the large language model in a real medical research context.

The invention provides a quantitative evaluation method for a mechanical loss change rule of a front gearbox. The quantitative evaluation method comprises the following steps: S1, comprehensively acquiring basic parameters; s2, determining the composition of mechanical loss, and constructing a total loss model; s3, construction and interactive design of a fusion algorithm; s4, training a fusion model; s5, carrying out mechanical loss quantitative calculation; s6, analyzing a mechanical loss change rule; and S7, verifying and correcting the model. According to the invention, through close connection and data closed loop among the steps, a full-process closed-loop evaluation system of data acquisition, model establishment, algorithm fusion, training optimization, quantitative calculation, rule extraction and verification correction is constructed, and full-process evaluation of mechanical loss from accurate quantification to rule mining is realized. And comprehensive technical support is provided for gearbox energy efficiency optimization.

The invention discloses an intelligent pediatric nursing teaching AI inquiry system and method based on a digital background, and relates to the crossing field of education informatization and artificial intelligence. The system comprises a front-end interaction module, a voice processing module, a teaching knowledge base module, an intelligent question and answer engine module, a teaching evaluation and feedback module, a background management module, a data analysis module and a virtual simulation operation linkage module, and the teaching knowledge base integrates on-duty competition certificates and traditional Chinese medicine pediatric characteristic knowledge and supports knowledge graph and vectorization retrieval; the intelligent question and answer engine adopts a retrieval enhancement generation technology and is combined with a standardized inquiry dialogue state machine to guarantee the answer accuracy. The method comprises the steps of case selection, multi-modal interaction, intelligent question and answer, process evaluation, virtual simulation linkage, adaptive recommendation and the like. According to the pediatric nursing teaching system, simulated inquiry training, refined process evaluation and teaching ecological closed-loop optimization are realized, the professionality, safety and individuation of pediatric nursing teaching are improved, and core ability cultivation of nursing talents is assisted.

The invention discloses an environment self-adaptive adjustment pipeline plugging process evaluation device and method, a plugging material is plugged in a second cavity through a closed space established by an evaluation pipe body and two sealing structures, an external gas source is connected to a gas introduction structure, and an external liquid source is connected to a liquid introduction structure. A gas leading-in structure, a liquid leading-in structure, a liquid leading-out structure, a first pressure gauge and a second pressure gauge are adopted to adjust the pressure and the liquid volume in the evaluation pipe body; the inclination angle of the evaluation pipe body is adjusted by controlling the lifting device, the test temperature is adjusted through the temperature control device, and finally performance evaluation of the plugging process under different working conditions is achieved. The device is simple in structure, and performance parameters such as limit plugging pressure, plugging time and the like of various plugging materials under different pipe diameters, materials, media, pressures, temperatures and gradients can be obtained. The problem that various performances of a pipeline plugging process have no clear index parameters is solved, and a plugging technical scheme under different working conditions is provided for field plugging operation.

The present invention relates to the technical field of human factors engineering and intelligent evaluation, and specifically provides a method and system for processing evaluation data of interruption response capabilities. The method includes constructing an experimental process scheduling structure that includes a primary task and an interruption task, collecting and constructing a complete behavior data stream, extracting time features during task switching and recovery, performing standardization and perturbation annotation, conducting factor analysis in combination with task labels, and generating a set of ability factor parameters. Subsequently, a scoring template is matched to calculate the individual interruption response ability score, a grade label is generated based on the score, and task ability adaptation and recommendation are completed. This method realizes the structuring, quantification, and closed-loop feedback of ability evaluation, and improves the evaluation accuracy and the intelligent level of task matching.

An intelligent evaluation and repair system and method for polluted soil and water. The system includes a monitoring and data collection module, a No. 1 decision maker, a cloud model recommendation module, a No. 2 decision maker, a No. 3 decision maker, a fixed-period regulation system, a variable-period regulation system, and a construction system. The output end of the monitoring and data collection module is connected to the input end of the No. 1 decision maker. The output end of the No. 1 decision maker is respectively connected to the input end of the cloud model recommendation system and the loop end port. The output end of the cloud model recommendation system is connected to the input end of the No. 2 decision maker. The output end of the No. 2 decision maker is respectively connected to the input ends of the No. 3 decision maker and the construction system. The purpose of the present invention is to solve the technical problems existing in the prior art that the repair processes and equipment are difficult to meet the major requirements of engineering and intelligence, the single construction period repair cycle, and the lack of intelligent control based on process evaluation, resulting in an overly rigid repair process.

The invention provides an ammonia-doped combustion full-process intelligent evaluation method and system for a coal power unit, and relates to the technical field of process evaluation, and the method comprises the steps: collecting historical engineering cost data, real-time market data and incentive measure data, and obtaining a data set; calling an ammonia fuel preparation cost model based on the input parameters to generate a preparation cost result; an ammonia fuel conveying path is matched based on the input parameters and the preparation cost result, and an optimal path scheme is generated; and according to the optimal path scheme, calling an intelligent interaction body to realize evaluation process scheduling, and outputting a comprehensive evaluation report including a carbon emission reduction economic result. According to the invention, the technical problem of poor scientific decision feasibility of a coal power unit ammonia doping technology in the prior art can be solved, and the technical goal of constructing an ammonia-doped combustion economy intelligent evaluation system which can be dynamically updated, driven by multi-source data and covered by a whole process is achieved; the technical effects of assisting the user to quantify the carbon emission reduction value and optimizing the investment strategy are achieved.

The present application relates to the technical field of medical instrument disinfection, in particular to a medical instrument cleaning and disinfection process evaluation system, which comprises an instrument entrance identification module, a material bacteria spectrum adaptation module, a use disinfection path reconstruction module, a combined instrument standard comparison module and a disinfection intensity fitting verification module.In the present application, the state of the instrument entering the process is accurately identified through synchronous verification of the instrument binding code, serial number and response timing, and the matching rules between the heat conductivity, texture grade and bacteria toxicity are combined to determine the objects that cannot be directly disinfected.Based on the historical use trajectory and the deviation score, a disinfection mode set is dynamically constructed, the consistent mode number in the combined processing is selected through the intersection comparison between the mode conditions, and the mode parameters and instrument requirement values are further compared as needed to realize the full-process adaptation and verification of the path selection, mode condition and processing intensity, and to enhance the matching rationality and execution consistency in the multi-instrument processing process.

The application discloses a tunnel construction whole-process evaluation method, system and equipment under a sensor network, relates to the technical field of geotechnical engineering structure health monitoring, and comprises the following steps: multiple types of sensors are arranged at each stage of tunnel construction and operation; multiple-source monitoring data streams of settlement, temperature, soil pressure and stress and strain are collected; after denoising, space-time alignment and fusion processing, a multi-dimensional data set is constructed in combination with geological construction and material data; a special dynamic evaluation model is established in stages; the safety state of the structure is quantitatively evaluated; and real-time early warning of an abnormal state is completed according to the evaluation result. The application solves the technical problems that the whole-life-cycle segmented evaluation is fragmented, the multiple-source monitoring data is chaotic, the hidden risk identification is lagging, and the safety state cannot be dynamically quantified in the safety control of tunnel construction, achieves dynamic control of the safety state of the whole process of tunnel construction, early warning of potential hidden dangers, and provides a reliable basis for construction risk prevention and control.