135 results about "Process evaluation" patented technology

The invention relates to the technical field of model construction, in particular to a three-dimensional model generation method and system based on a lightweight glass container. The method comprises the following steps: performing information acquisition on a lightweight glass container by using a preset multi-mode scanning sensor, acquiring a multi-view visible light image, depth information and structured light projection data, and constructing a standard multi-view point cloud data set; performing multi-modal fusion based on the standard multi-view point cloud data set to obtain multi-modal fusion data of the glass container; performing thin-wall judgment on the multi-mode fusion data of the glass container, and repairing a thin-wall structure to obtain a high-integrity three-dimensional point cloud model; therefore, through multi-modal data fusion, geometric and optical joint optimization and a multi-scale path evaluation mechanism, the problems of low structure reconstruction precision, large transparent material error and process evaluation deficiency in traditional glass container modeling are solved, and the geometric fidelity, the material reduction degree and the construction whole process controllability of the three-dimensional model are improved.

The invention provides an artificial intelligence-based etching process evaluation method and system, and relates to the technical field of artificial intelligence. The method comprises the following steps: firstly, determining a semantic vector of a photoetching pattern; secondly, through a vector space conversion unit included in the etching process evaluation network, carrying out space conversion operation on the photoetching pattern semantic vector, and outputting a corresponding photoetching pattern conversion vector; and then, according to the photoetching pattern conversion vector, through an etching process evaluation unit included in the etching process evaluation network, carrying out combined mining and evaluation operation on multiple local etching processes included in the target etching process, and outputting target process evaluation data corresponding to the target etching process. On the basis of the content, the problem that in the prior art, the efficiency and reliability of etching process evaluation are relatively low can be solved.

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 photovoltaic energy storage management system based on an Internet of Things terminal, and relates to the technical field of photovoltaic energy storage, and the system comprises a management center which is in communication connection with a photovoltaic energy storage module, an Internet of Things module, a process data processing module and a process evaluation module. Corresponding Internet of Things terminals are arranged on a photovoltaic power generation unit and a photovoltaic energy storage unit respectively, process data of the photovoltaic power generation unit and the photovoltaic energy storage unit are collected in real time, and a photovoltaic energy storage module is decomposed into two independent parts. The method comprises the steps of obtaining process data of a photovoltaic power generation unit and a photovoltaic energy storage unit, performing corresponding stage evaluation on the two independent parts according to the obtained process data to obtain corresponding stage evaluation coefficients, and judging whether the corresponding energy efficiency of the photovoltaic power generation unit and the photovoltaic energy storage unit is normal or not according to the obtained stage evaluation coefficients so as to realize respective monitoring of the two independent parts.

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 mainly provides a production activity comprehensive evaluation method based on multi-dimensional indexes. The method comprises the following steps: carrying out dimension division on enterprise production activity data according to six indexes including safety, quality, cost, delivery, environment and mastitis; respectively defining a first-level index and a second-level index decomposed according to the first-level index under each dimension, and formulating calculation logic of each index; utilizing correlation analysis to find out correlation indexes with high correlation degree with the first-level indexes from a large number of second-level indexes; calculating the weight corresponding to each correlation index through the information entropy of the correlation indexes; by establishing a comprehensive evaluation model, index scores of all dimensions are calculated, actual data of monthly production activities are visually presented, and enterprises are guided to carry out production process evaluation. According to the technical scheme provided by the invention, the purpose of comprehensively evaluating the operation condition of the enterprise can be achieved by defining the indexes of multiple dimensions.

The invention relates to the technical field of optical fiber patch cord manufacturing, and provides a multi-core optical fiber fan-in and fan-out patch cord manufacturing system which comprises an optical fiber adsorption module, an arrangement module, an end face machining module, a base butt joint module and a process evaluation module. The arrangement module adjusts the distance between the at least two adsorbed optical fibers, the end face processing module processes the at least two arranged optical fiber cores to expose the connecting end portions of the at least two optical fiber cores, and the base butt joint module conducts butt joint placement on the connecting end portions of the at least two optical fibers and a processing base. The process evaluation module collects the arrangement state data of the optical fiber adsorption module, evaluates the arrangement state according to the state data to form an evaluation result, and triggers the arrangement module to adjust the distance between the at least two optical fibers.

The invention discloses a digital-real fusion test method and system for aerospace equipment manufacturing, and belongs to the field of aerospace equipment manufacturing, and the method comprises the steps: designing an aerospace equipment digital twinborn resource library module which comprises a material library unit, a modeling simulation unit and a process evaluation unit, wherein the material unit provides a metal or non-metal material for equipment manufacturing, the modeling simulation unit is responsible for establishing a three-dimensional model of equipment and completing coupled physical field simulation, and the process evaluation unit stores process parameters and equipment energy efficiency data in the equipment manufacturing process; designing an aerospace equipment iterative optimization module, wherein the module completes equipment structure optimization and equipment manufacturing process optimization based on a multi-model collaborative optimization strategy; and an aerospace equipment data-real fusion consistency verification module is designed, and the module synchronizes resource library data and completes data-real consistency verification after data migration of the aerospace equipment based on data-real real-time interaction. The method disclosed by the invention can effectively improve the manufacturing process efficiency of aerospace equipment and shorten the production cycle.

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 provides a spaceflight launch mission evaluation method and system, and the method comprises the steps: dividing a spaceflight launch mission into a plurality of rocket flight segments, and carrying out the evaluation of a subsystem level, a rocket level and a key action in each rocket flight segment. Performing task level evaluation by combining the previous evaluation result, the parameter value of the injection parameter and the like after satellite-rocket separation to obtain a final task evaluation result of the spaceflight launch task; wherein the evaluation of the evaluation elements in the subsystems and the evaluation of the subsystems are realized by using a process evaluation criterion, and the evaluation of the subsystem level, the rocket level and the key action is realized by using a result evaluation criterion. According to the scheme disclosed by the invention, each level can take the most direct and most critical result index as an evaluation basis from the whole to the part, so that subsequent improvement and optimization are effectively guided.

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.

The invention relates to a learning evaluation method and device, equipment and a storage medium. The method comprises the steps that activity data of students on a teaching platform system are acquired according to the needs of a preset learning evaluation framework; processing the activity data according to a preset rule to obtain processed data; and determining a learning condition and evaluation for the student based on the processed data. The learning evaluation framework predetermined by professionals can effectively fuse process evaluation, result evaluation, value-added evaluation and comprehensive evaluation, and can deeply and scientifically analyze the learning performance of the students based on the operation behaviors and learning data of the students, thereby making accurate evaluation and giving constructive suggestions, and improving the learning efficiency of the students. Therefore, students can be well helped to know their learning conditions and adjust learning states and strategies.

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.