Personal physical attainment evaluation management method and system

Abstract

The invention provides a personal physical attainment evaluation management method and system, and the method comprises the steps: initializing an evaluation index system of personal physical attainment, carrying out the dimension classification of all evaluation indexes in the evaluation index system, and obtaining a plurality of evaluation dimensions of the personal physical attainment; extracting the index judgment value of the user in each evaluation dimension, and generating an index judgment matrix of the user physical attitudes by using all the index judgment values; setting a personalized membership function of personal physical attitudes based on the index type of each evaluation index, and performing membership evaluation on the evaluation levels of the physical attitudes of the user by using the personalized membership function in combination with the index judgment matrix to obtain the membership degree of the user to each evaluation level in the evaluation index system; and determining the confidence membership level of the user physical attainment evaluation through all the membership degrees, and generating a multi-dimensional evaluation result of the user physical attainment based on the confidence membership level. Based on the scheme, multi-dimensional membership evaluation of personal physical attainment can be realized.

Description

Technical Field

[0001] The present application relates to the technical field of assessment process management, and more specifically, to a personal sports literacy assessment management method and system. Background Art

[0002] In recent years, with the improvement of the comprehensive understanding of sports literacy, the evaluation system has begun to expand in multiple dimensions, incorporating sports cognition, psychological quality and sports behavior into the consideration scope. The evaluation of personal sports literacy is in a stage of rapid development and improvement.

[0003] Traditional sports literacy assessments focus on a single dimension, only considering physical fitness or sports skills, while ignoring the assessment of key areas such as sports cognition, psychological quality and sports behavior. For example, measuring students' sports literacy only by physical fitness test scores ignores their understanding of sports rules, their ability to adjust psychologically when facing competition pressure, and their enthusiasm for daily participation in sports activities. This one-sided assessment method makes it difficult to outline the overall picture of an individual's sports literacy and cannot accurately reflect their true level. It is easy to lead to misjudgment of individual sports ability and is not conducive to targeted training and improvement. Therefore, how to achieve multi-dimensional affiliation assessment of personal sports literacy has become a difficult problem faced by the industry. Summary of the invention

[0004] The present application provides a personal sports literacy evaluation management method and system, which can realize multi-dimensional affiliation evaluation of personal sports literacy.

[0005] In a first aspect, the present application provides a method for evaluating and managing personal physical literacy, comprising:

[0006] Acquire multiple evaluation indicators of personal sports literacy, initialize the evaluation indicator system of personal sports literacy based on each evaluation indicator, classify all evaluation indicators in the evaluation indicator system into dimensions, and obtain multiple evaluation dimensions of personal sports literacy;

[0007] Collecting the evaluation index data of the user's physical literacy in a historical period, and preprocessing the evaluation index data, extracting the user's index judgment value in each evaluation dimension from the preprocessed evaluation index data, and then using all the index judgment values ​​to generate an index judgment matrix of the user's physical literacy;

[0008] Based on the indicator type of each evaluation indicator, a personalized membership function of personal sports literacy in the membership evaluation is set, and the personalized membership function is used in combination with the indicator judgment matrix to perform a membership evaluation on the evaluation level of the user's sports literacy to obtain the user's membership degree to each evaluation level in the evaluation indicator system;

[0009] Determine the confidence membership level of the user's sports literacy evaluation through all membership degrees, and then generate a multi-dimensional evaluation result of the user's sports literacy based on the confidence membership level.

[0010] In some embodiments, dimension classification is performed on all evaluation indicators in the evaluation index system, and the specific multiple evaluation dimensions of personal sports literacy obtained include:

[0011] Obtain all evaluation indicators in the evaluation index system;

[0012] Perform multi-dimensional clustering on all evaluation indicators to obtain multiple indicator clustering clusters;

[0013] Perform dimension classification on each indicator clustering cluster to obtain multiple evaluation dimensions of personal sports literacy.

[0014] In some embodiments, the preprocessing includes data cleaning, normalization processing, and quantification of qualitative indicators.

[0015] In some embodiments, extracting the index judgment values of the user in each evaluation dimension from the preprocessed evaluation index data specifically includes:

[0016] For each evaluation dimension, obtain the measured mean value of each evaluation indicator of the user in the evaluation dimension from the preprocessed evaluation index data;

[0017] Compare and score each measured mean value with the standard value of each evaluation indicator to obtain the index score value of each evaluation indicator of the user;

[0018] Determine the index judgment value of the user in the evaluation dimension through all the index score values, and then obtain the index judgment values of the user in each evaluation dimension.

[0019] In some embodiments, using all the index judgment values to generate an index judgment matrix of the user's sports literacy specifically includes:

[0020] Obtain multiple evaluation grades of personal sports literacy in the evaluation index system;

[0021] Construct an index judgment matrix of the user's sports literacy based on each evaluation grade and all the index judgment values.

[0022] In some embodiments, using the personalized membership function to perform membership evaluation on the evaluation grades of the user's sports literacy in combination with the index judgment matrix, and obtaining the membership degrees of the user for each evaluation grade in the evaluation index system specifically includes:

[0023] Obtain the membership function of each evaluation indicator from the personalized membership function;

[0024] For each evaluation level in the evaluation index system, use each membership function to determine the membership value of each evaluation index of the user to the evaluation level;

[0025] Determine the membership degree of the user to the evaluation level through all the membership values, and then obtain the membership degree of the user to each evaluation level in the evaluation index system.

[0026] In some embodiments, determining the confidence membership level of the user's physical fitness evaluation through all the membership degrees is to use the evaluation level with the highest membership degree in the evaluation index system as the confidence membership level of the user's physical fitness evaluation.

[0027] In a second aspect, the present application provides a personal physical fitness evaluation management system, including a management unit, and the management unit includes:

[0028] An acquisition module, configured to acquire multiple evaluation indexes of personal physical fitness, initialize an evaluation index system of personal physical fitness based on each evaluation index, classify all evaluation indexes in the evaluation index system by dimension, and obtain multiple evaluation dimensions of personal physical fitness;

[0029] A processing module, configured to collect evaluation index data of the user's physical fitness in a historical time period, preprocess the evaluation index data, extract index judgment values of the user in each evaluation dimension from the preprocessed evaluation index data, and then generate an index judgment matrix of the user's physical fitness using all the index judgment values;

[0030] The processing module is further configured to set a personalized membership function for personal physical fitness in membership evaluation based on the index type of each evaluation index, and use the personalized membership function to combine the index judgment matrix to perform membership evaluation on the evaluation level of the user's physical fitness, and obtain the membership degree of the user to each evaluation level in the evaluation index system;

[0031] An execution module, configured to determine the confidence membership level of the user's physical fitness evaluation through all the membership degrees, and then generate a multi-dimensional evaluation result of the user's physical fitness based on the confidence membership level.

[0032] In a third aspect, the present application provides a computer device, which includes a memory and a processor. The memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned personal physical fitness evaluation management method.

[0033] In a fourth aspect, the present application provides a computer-readable storage medium, in which instructions or codes are stored. When the instructions or codes are run on a computer, the computer is caused to execute the above-mentioned personal physical fitness evaluation management method.

[0034] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0035] In a personal sports literacy evaluation management method and system provided by this application, multiple evaluation indicators of personal sports literacy are obtained, and an evaluation index system of personal sports literacy is initialized based on each evaluation indicator. All evaluation indicators in the evaluation index system are classified by dimension to obtain multiple evaluation dimensions of personal sports literacy; the evaluation index data of the user's sports literacy in a historical time period is collected, and the evaluation index data is preprocessed. Index judgment values of the user in each evaluation dimension are extracted from the preprocessed evaluation index data, and then an index judgment matrix of the user's sports literacy is generated using all the index judgment values; a personalized membership function of personal sports literacy in the membership evaluation is set based on the index type of each evaluation indicator, and the membership evaluation of the user's sports literacy evaluation level is performed using the personalized membership function in combination with the index judgment matrix to obtain the membership degrees of the user for each evaluation level in the evaluation index system; the confidence membership level of the user's sports literacy evaluation is determined through all the membership degrees, and then a multi-dimensional evaluation result of the user's sports literacy is generated based on the confidence membership level.

[0036] Thus, in this application, the confidence membership level of the user's sports literacy evaluation is determined through all the membership degrees, and then a multi-dimensional evaluation result of the user's sports literacy is generated based on the confidence membership level; First, by determining the index judgment matrix, the quantitative performance data of the user in each evaluation dimension can be obtained, providing a structured input basis for the subsequent membership evaluation. The construction of the index judgment matrix not only retains the original characteristics of the indicators in each dimension but also reveals the internal correlation between the indicators through matrix operations, making multi-dimensional comparative analysis possible. When the index judgment matrix is combined with the weight coefficient, the comprehensive score of the user in a specific dimension can be quickly calculated, providing accurate data support for the subsequent fuzzy evaluation. At the same time, the matrix structure is convenient for computer processing, greatly improving the efficiency of large-scale population evaluation and making it a reality to track the development of personal sports literacy in real-time and dynamically; Second, by determining the'membership degree', the probability distribution of the user reaching each evaluation level can be obtained, realizing a scientific conversion from quantitative data to qualitative evaluation, effectively solving the boundary effect problem caused by the rigid grading in traditional evaluations, and being able to more delicately reflect the user's true level. By analyzing the membership degree distribution of each evaluation dimension, not only can the current literacy level of the user be judged, but also their dominant dimensions and areas to be improved can be identified. It can ensure that the evaluation result contains both quantitative membership probabilities and qualitative grade descriptions, providing a dual basis for the formulation of personalized sports guidance programs. At the same time, the continuous change characteristic of the membership degree is also convenient for tracking the user's progress trajectory and realizing developmental evaluation; In summary, based on the above solutions, a multi-dimensional membership evaluation of personal sports literacy can be realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0038] Figure 1 is an exemplary flowchart of a personal sports literacy evaluation management method according to some embodiments of the present application;

[0039] Figure 2 is a schematic flowchart of determining membership degrees according to some embodiments of the present application;

[0040] Figure 3 is a schematic structural diagram of a management unit according to some embodiments of the present application;

[0041] Figure 4 is a schematic structural diagram of a computer device for implementing the personal sports literacy evaluation management method according to some embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] In order to better understand the technical solutions of the present application, the following will detail the technical solutions of the present application in combination with the drawings in the specification and specific embodiments.

[0043] Refer to Figure 1 , which is an exemplary flowchart of a personal sports literacy evaluation management method according to some embodiments of the present application. The personal sports literacy evaluation management method mainly includes the following steps:

[0044] In step 101, multiple evaluation indicators of personal sports literacy are obtained, an evaluation index system of personal sports literacy is initialized based on each evaluation indicator, and all evaluation indicators in the evaluation index system are classified by dimension to obtain multiple evaluation dimensions of personal sports literacy.

[0045] It should be noted that in this application, the evaluation index system is a systematic evaluation framework composed of a specific structure and weight relationship; the evaluation indexes are specific observation items and measurement criteria used to measure and evaluate the development level of an individual's sports literacy; in specific implementation, first, key indexes are screened through literature research, expert interviews and existing sports evaluation standards (such as: National Student Physical Health Standard) to ensure coverage of dimensions such as physical function, motor skills, health knowledge, sports behavior and sports morality. For example, physical function can include quantifiable indexes such as vital capacity, grip strength, flexibility, etc., motor skills can cover basic items such as 50-meter run, standing long jump, etc., health knowledge can be evaluated through theoretical examinations, sports behavior records the frequency and intensity of sports, and sports morality is combined with coach scoring and team mutual evaluation; then, a hierarchical structure model is established, the overall goal is decomposed into a criterion layer and an index layer, and then an expert questionnaire is designed to collect judgments on the importance degree of each evaluation index; then, a professional software is used to calculate the weight coefficients of each evaluation index, and the scientific nature of the weights is ensured through consistency tests, and an initial evaluation index system including 5 first-level dimensions, 20 second-level indexes and corresponding weight coefficients is formed as the evaluation index system of an individual's sports literacy.

[0046] In some embodiments, the dimension classification of all evaluation indexes in the evaluation index system to obtain multiple evaluation dimensions of an individual's sports literacy can be implemented by the following steps:

[0047] Obtain all evaluation indexes in the evaluation index system;

[0048] Perform multi-dimensional clustering on all evaluation indexes to obtain multiple index clustering clusters;

[0049] Perform dimension classification on each index clustering cluster to obtain multiple evaluation dimensions of an individual's sports literacy.

[0050] It should be noted that in this application, the evaluation dimension is the main framework for constructing the evaluation system, and this evaluation dimension can be used to establish the logical structure of the comprehensive evaluation. Specifically, when implementing, first, all evaluation indicators are obtained from the evaluation index system. Then, the K-means clustering algorithm can be used to perform multi-dimensional feature analysis on all evaluation indicators, project each evaluation indicator into a high-dimensional feature space, determine the optimal number of clusters through the silhouette coefficient method, and group evaluation indicators with high similarity into the same cluster according to the measurement methods, fields of belonging, and mutual relationships of each evaluation indicator, so as to obtain multiple indicator clusters. For example, physiological indicators such as vital capacity and grip strength are grouped into one category, and sports skill indicators such as basketball dribbling and football shooting are grouped into another category. Finally, based on the clustering results and the sports education theory framework, the expert group can perform semantic analysis and concept definition on each indicator cluster, and use the Delphi method for multiple rounds of demonstration to finally determine the evaluation dimension corresponding to each cluster. For example, the physiological indicator cluster is classified as the physical function dimension, and the sports skill cluster is classified as the sports ability dimension, so as to obtain multiple evaluation dimensions of personal sports literacy.

[0051] In step 102, the evaluation index data of the user's sports literacy in the historical time period is collected, and the evaluation index data is preprocessed. The index judgment values of the user in each evaluation dimension are extracted from the preprocessed evaluation index data, and then the index judgment matrix of the user's sports literacy is generated using all the index judgment values.

[0052] It should be noted that in this application, the evaluation index data carries the specific performance information of the user in each dimension, and the preprocessing includes data cleaning, normalization processing, and quantification of qualitative indicators. Specifically, when implementing, the multi-source heterogeneous data collection technology is adopted to record the physiological data such as the user's heart rate and exercise duration in real time through intelligent wearable devices in the historical time period (by default, the most recent month), obtain the user's exercise trajectory and exercise frequency in the historical time period using the sports application program interface, extract the user's theoretical test scores and skill assessment results in the historical time period in combination with the sports teaching management system, and at the same time collect the behavioral performance data related to sports morality through a customized questionnaire, so as to use the set of physiological data, exercise trajectory, exercise frequency, theoretical test scores, skill assessment results, and behavioral performance data as the evaluation index data of sports literacy. Then, outlier detection and correction are performed on the collected original data, the sliding window algorithm is used to identify and eliminate sensor false alarm data, the missing values are processed by the multiple imputation method to ensure data integrity, then the index data with different dimensions is standardized, and all types of indicators are uniformly converted to the evaluation scale of 0-100 points, and finally data normalization is performed to eliminate the dimension difference between indicators, and the preprocessing of the evaluation index data is completed.

[0053] In some embodiments, extracting the index judgment values of the user in each evaluation dimension from the preprocessed evaluation index data can be achieved through the following steps:

[0054] For each evaluation dimension, obtain the measured mean value of each evaluation index of the user in the evaluation dimension from the preprocessed evaluation index data;

[0055] Compare and score each measured mean value with the standard value of each evaluation index to obtain the index score value of each evaluation index of the user;

[0056] Determine the index judgment value of the user in the evaluation dimension through all the index score values, and then obtain the index judgment values of the user in each evaluation dimension.

[0057] It should be noted that in this application, the index judgment value represents the comprehensive ability level of the user in each evaluation dimension; the measured mean value is a quantitative value reflecting the true level of each evaluation index of the user within a specific time period; the index score value is an intermediate result of converting the measured performance into a standardized score, and this index score value can achieve comparability between different evaluation indexes;

[0058] Specifically, when implementing, first, for each evaluation dimension, obtain all the measured values of each evaluation index of the user in the evaluation dimension from the preprocessed evaluation index data. For each rating index in the evaluation dimension, take the average of all the measured values of all the rating indexes as the measured mean value of the user in the evaluation index. Through the above method, the measured mean values of each evaluation index of the user in the evaluation dimension can be obtained; then, for each evaluation index, obtain the standard score of the evaluation index from the standard library of personal sports literacy, and thus take the ratio of the measured mean value of the evaluation index to the standard score as the index score value of the user's evaluation index. Through the above method, the index score values of each evaluation index of the user can be obtained; finally, obtain the influence weight of each evaluation index in the evaluation dimension from the standard library of personal sports literacy, and thus take each influence weight as the weight to calculate the weighted sum of all the index score values as the index judgment value of the user in the evaluation dimension. Through the above method, the index judgment values of the user in each evaluation dimension can be obtained.

[0059] In some embodiments, generating an index judgment matrix of the user's sports literacy using all the index judgment values can be achieved through the following steps:

[0060] Obtain multiple evaluation levels of personal sports literacy in the evaluation index system;

[0061] Construct an index judgment matrix of the user's sports literacy based on each evaluation level and all the index judgment values.

[0062] It should be noted that in this application, the index judgment matrix is a matrix that quantifies the possibility of a user reaching different levels in each dimension. When specifically implemented, first, multiple evaluation levels of personal sports literacy in the evaluation index system are obtained from the standard library of personal sports literacy. This evaluation level is to establish a classification standard system for sports literacy levels, and each evaluation level corresponds to index judgment values in different intervals. Then, an empty judgment matrix is initialized, with the evaluation levels as the rows in the judgment matrix and the index judgment values as the columns in the judgment matrix, so that the filled judgment matrix is used as the index judgment matrix of the user's sports literacy.

[0063] In step 103, based on the index types of each evaluation index, a personalized membership function of personal sports literacy in the membership evaluation is set, and the membership evaluation of the user's sports literacy evaluation level is performed using the personalized membership function in combination with the index judgment matrix to obtain the membership degrees of the user for each evaluation level in the evaluation index system.

[0064] In some embodiments, setting the personalized membership function of personal sports literacy in the membership evaluation based on the index types of each evaluation index can be implemented in the following manner, that is: based on the theories of sports measurement and exercise physiology, differential membership functions are designed for different types of evaluation indexes. For quantitative indexes such as physical fitness test data, a piecewise linear membership function is adopted, and the threshold intervals of each level are set according to national standards; for qualitative indexes such as sports moral evaluation, a trapezoidal membership function is adopted, and the transition interval is determined through expert scoring. A membership function parameter database is established to support automatic matching of corresponding function parameters according to different age groups and genders to ensure the accuracy of the evaluation. For example, the excellent level threshold of the vital capacity index is set to the level of the top 15% of the same age group. Through the above method, the membership functions of each evaluation index can be set, and thus the set of all membership functions is used as the personalized membership function of personal sports literacy in the membership evaluation. It should be noted that in this application, the personalized membership function is a mathematical tool for converting the measured values of indexes designed for different types of evaluation indexes into the possibility of levels.

[0065] In some embodiments, the membership evaluation of the user's sports literacy evaluation level is performed using the personalized membership function in combination with the index judgment matrix to obtain the membership degrees of the user for each evaluation level in the evaluation index system. Refer to Figure 2 as described above. This figure is a schematic flowchart of determining the membership degree in some embodiments of this application. In this embodiment, the determination of the membership degree can be implemented by the following steps:

[0066] In step 1031, the membership functions of each evaluation index are obtained from the personalized membership function;

[0067] In step 1032, for each evaluation level in the evaluation index system, membership functions are used to determine the membership values of each evaluation index of the user for the evaluation level;

[0068] In step 1033, the membership degree of the user for the evaluation level is determined through all the membership values, and then the membership degrees of the user for each evaluation level in the evaluation index system are obtained.

[0069] It should be noted that in this application, the membership degree reflects the comprehensive probability that the user reaches each evaluation level as a whole; the membership function is a mathematical tool for converting the measured values of the indexes into the possibility of levels; the membership value represents the probability that a single evaluation index belongs to each evaluation level.

[0070] In specific implementation, first, the membership functions of each evaluation index are obtained from the personalized membership functions; then, for each evaluation level in the evaluation index system, the standardized scores of the user on each evaluation index are input into the corresponding membership function, and the membership values of each evaluation index for the evaluation level can be obtained through function operations. This calculation process uses fuzzy inference technology to handle the transition situation when the index score is at the level boundary and can establish a multi-level verification mechanism. When the membership value distribution of a certain evaluation index is abnormal, the data collection and preprocessing links are automatically checked. For example, for a student with a 50-meter running result of 7.8 seconds, the membership value for the excellent level is calculated as 0.6 and the membership value for the good level is 0.4 through the membership function; finally, the mean value of all membership values can be used as the membership degree of the user for the evaluation level.

[0071] In step 104, the confidence membership level of the user's physical fitness evaluation is determined through all the membership degrees, and then a multi-dimensional evaluation result of the user's physical fitness is generated based on the confidence membership level.

[0072] In some embodiments, determining the confidence membership level of the user's physical fitness evaluation through all the membership degrees is to take the evaluation level with the highest membership degree in the evaluation index system as the confidence membership level of the user's physical fitness evaluation.

[0073] In some embodiments, generating the multi-dimensional evaluation result of the user's physical fitness based on the confidence membership level can be implemented in the following manner, that is: obtaining the multi-dimensional evaluation criteria of the user's physical fitness from the standard library of personal physical fitness, and obtaining the comprehensive performance evaluation corresponding to the confidence membership level from the multi-dimensional evaluation criteria as the multi-dimensional evaluation result of the user's physical fitness.

[0074] In addition, on the other hand of this application, in some embodiments, this application provides a personal physical fitness evaluation management system, which includes a management unit. Refer to Figure 3, which is a schematic structural diagram of a management unit shown in some embodiments of the present application. The management unit includes: an acquisition module 201, a processing module 202, and an execution module 203, which are described as follows:

[0075] The acquisition module 201. In the present application, the acquisition module 201 is mainly used to acquire multiple evaluation indicators of personal sports literacy, initialize an evaluation indicator system of personal sports literacy based on each evaluation indicator, classify all evaluation indicators in the evaluation indicator system by dimension, and obtain multiple evaluation dimensions of personal sports literacy;

[0076] The processing module 202. In the present application, the processing module 202 is used to collect evaluation indicator data of a user's sports literacy in a historical time period, preprocess the evaluation indicator data, extract index judgment values of the user in each evaluation dimension from the preprocessed evaluation indicator data, and then generate an index judgment matrix of the user's sports literacy using all the index judgment values;

[0077] It should be noted that the processing module 202 is also used to set a personalized membership function of personal sports literacy in membership evaluation based on the index types of each evaluation indicator, and use the personalized membership function to combine the index judgment matrix to perform membership evaluation on the evaluation level of the user's sports literacy, so as to obtain the membership degrees of the user for each evaluation level in the evaluation indicator system;

[0078] The execution module 203. In the present application, the execution module 203 is mainly used to determine the confidence membership level of the user's sports literacy evaluation through all the membership degrees, and then generate a multi-dimensional evaluation result of the user's sports literacy based on the confidence membership level.

[0079] The above has introduced in detail the examples of the personal sports literacy evaluation management method and system provided by the embodiments of the present application. It can be understood that, in order to implement the above functions, the corresponding device includes the corresponding hardware structure and / or software module for executing each function. Those skilled in the art should easily realize that, combining the units and algorithm steps of each example described in the embodiments disclosed in this article, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraint conditions of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0080] In some embodiments, the present application also provides a computer device, which includes a memory and a processor. The memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned personal sports literacy evaluation management method.

[0081] In some embodiments, referring to Figure 4 , the dashed lines in the figure indicate that the unit or module is optional. This figure is a schematic structural diagram of a computer device for implementing the personal sports literacy evaluation management method according to an embodiment of the present application. The personal sports literacy evaluation management method described in the above embodiments can be implemented by Figure 4 the computer device shown. The computer device includes at least one processor 301, a memory 302, and at least one communication unit 305. The computer device can be a terminal device, a server, or a chip.

[0082] The processor 301 can be a general-purpose processor or a dedicated processor. For example, the processor 301 can be a central processing unit (CPU). The CPU can be used to control the computer device, execute software programs, and process the data of the software programs. The computer device can also include a communication unit 305 for implementing signal input (reception) and output (transmission).

[0083] For example, the computer device can be a chip, and the communication unit 305 can be the input and / or output circuit of the chip, or the communication unit 305 can be the communication interface of the chip. The chip can be a component of a terminal device, a network device, or other devices.

[0084] Again, for example, the computer device can be a terminal device or a server, and the communication unit 305 can be the transceiver of the terminal device or the server, or the communication unit 305 can be the transceiver circuit of the terminal device or the server.

[0085] One or more memories 302 can be included in the computer device. A program 304 is stored thereon. The program 304 can be run by the processor 301 to generate instructions 303, so that the processor 301 executes the method described in the above method embodiments according to the instructions 303. Optionally, data (such as a target audit model) can also be stored in the memory 302. Optionally, the processor 301 can also read the data stored in the memory 302. The data can be stored at the same storage address as the program 304, or the data can be stored at a different storage address from the program 304.

[0086] The processor 301 and the memory 302 can be provided separately or integrated together. For example, they can be integrated on a system on chip (SOC) of a terminal device.

[0087] It should be understood that the steps of the above method embodiments can be completed by the logic circuit in the form of hardware or the instructions in the form of software in the processor 301. The processor 301 can be a CPU, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices. For example, discrete gates, transistor logic devices or discrete hardware components.

[0088] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0089] For example, in some embodiments, the present application also provides a computer-readable storage medium, in which instructions or code are stored. When the instructions or code run on a computer, the computer is caused to execute the above-mentioned personal sports literacy evaluation management method.

[0090] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications to these embodiments once they learn the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present application.

[0091] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these modifications and variations.

Claims

1. A method for evaluating and managing personal sports literacy, characterized in that, It includes the following steps: Obtain multiple evaluation indicators of personal sports literacy, initialize the evaluation indicator system of personal sports literacy based on each evaluation indicator, classify all evaluation indicators in the evaluation indicator system by dimension, and obtain multiple evaluation dimensions of personal sports literacy; Collect the evaluation indicator data of the user's sports literacy in the historical time period, preprocess the evaluation indicator data, extract the index judgment values of the user in each evaluation dimension from the preprocessed evaluation indicator data, and then generate an index judgment matrix of the user's sports literacy using all the index judgment values; Set a personalized membership function of personal sports literacy in the membership evaluation based on the index types of each evaluation indicator, and use the personalized membership function combined with the index judgment matrix to conduct a membership evaluation on the evaluation level of the user's sports literacy, and obtain the membership degrees of the user to each evaluation level in the evaluation indicator system; Determine the confidence membership level of the user's sports literacy evaluation through all the membership degrees, and then generate a multi-dimensional evaluation result of the user's sports literacy based on the confidence membership level.

2. The method according to claim 1, wherein Classifying all evaluation indicators in the evaluation indicator system by dimension to obtain multiple evaluation dimensions of personal sports literacy specifically includes: Obtain all evaluation indicators in the evaluation indicator system; Perform multi-dimensional clustering on all evaluation indicators to obtain multiple indicator clustering clusters; Classify each indicator clustering cluster by dimension to obtain multiple evaluation dimensions of personal sports literacy.

3. The method according to claim 1, characterized in that, The preprocessing includes data cleaning, normalization processing, and quantification of qualitative indicators.

4. The method according to claim 1, characterized in that, Extracting the index judgment values of the user in each evaluation dimension from the preprocessed evaluation indicator data specifically includes: For each evaluation dimension, obtain the measured mean value of each evaluation indicator of the user in the evaluation dimension from the preprocessed evaluation indicator data; Compare and score each measured mean value with the standard value of each evaluation indicator to obtain the index score value of each evaluation indicator of the user; Determine the index judgment value of the user in the evaluation dimension through all the index score values, and then obtain the index judgment values of the user in each evaluation dimension.

5. The method according to claim 1, characterized in that, Generating an index judgment matrix of the user's sports literacy using all the index judgment values specifically includes: Obtain multiple evaluation levels of personal sports literacy in the evaluation indicator system; Construct an index judgment matrix of the user's sports literacy based on each evaluation level and all the index judgment values.

6. The method according to claim 1, characterized in that Using the personalized membership function combined with the index judgment matrix to conduct a membership evaluation on the evaluation level of the user's sports literacy, and obtaining the membership degrees of the user to each evaluation level in the evaluation indicator system specifically includes: Obtain the membership function of each evaluation indicator from the personalized membership function; For each evaluation level in the evaluation indicator system, use each membership function to determine the membership value of each evaluation indicator of the user to the evaluation level; Determine the membership degree of the user to the evaluation level through all the membership values, and then obtain the membership degrees of the user to each evaluation level in the evaluation indicator system.

7. The method according to claim 1, wherein Determining the confidence membership level of the user's sports literacy evaluation through all the membership degrees is to use the evaluation level with the highest membership degree in the evaluation indicator system as the confidence membership level of the user's sports literacy evaluation.

8. A personal sports literacy evaluation and management system, the personal sports literacy evaluation and management system includes a management unit, characterized in that, The management unit includes: An acquisition module, configured to acquire multiple evaluation indicators of an individual's physical education literacy, initialize an evaluation index system of the individual's physical education literacy based on each evaluation indicator, classify all evaluation indicators in the evaluation index system by dimension, and obtain multiple evaluation dimensions of the individual's physical education literacy; A processing module, configured to collect evaluation index data of the user's physical education literacy within a historical time period, preprocess the evaluation index data, extract index judgment values of the user in each evaluation dimension from the preprocessed evaluation index data, and then generate an index judgment matrix of the user's physical education literacy using all the index judgment values; The processing module is further configured to set a personalized membership function of the individual's physical education literacy in the membership evaluation based on the index type of each evaluation indicator, and perform a membership evaluation on the evaluation level of the user's physical education literacy by combining the personalized membership function with the index judgment matrix to obtain the membership degrees of the user for each evaluation level in the evaluation index system; An execution module, configured to determine a confidence membership level of the user's physical education literacy evaluation through all the membership degrees, and then generate a multi-dimensional evaluation result of the user's physical education literacy based on the confidence membership level.

9. A computer device, characterized in that, The computer device includes a memory and a processor. The memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the individual physical education literacy evaluation management method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Instructions or codes are stored in the computer-readable storage medium. When the instructions or codes run on a computer, the computer is caused to execute the individual physical education literacy evaluation management method according to any one of claims 1 to 7.

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