CN114242241A - Self-adaptive evaluation method for constitutional health groups of college students - Google Patents

Self-adaptive evaluation method for constitutional health groups of college students Download PDF

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CN114242241A
CN114242241A CN202111356260.9A CN202111356260A CN114242241A CN 114242241 A CN114242241 A CN 114242241A CN 202111356260 A CN202111356260 A CN 202111356260A CN 114242241 A CN114242241 A CN 114242241A
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寇月
李海
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Civil Aviation Flight University of China
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Abstract

The invention relates to the technical field of physical health assessment, in particular to a self-adaptive assessment method for physical health groups of college students, which comprises the following steps: 1) determining a final weight by using the least square aggregation subjective and objective weights; the method comprises the following steps: calculating subjective weight of the evaluation attribute based on AHP; calculating an evaluation attribute objective weight based on the CRITIC; the synthetic weights are calculated based on a least squares ensemble. 2) Evaluating the health weighted TOPSIS of the constitution of the college students based on the comprehensive index representation; the method comprises the following steps: establishing a decision matrix, constructing a weighted decision matrix, determining positive and negative ideal solutions, calculating distances, and judging the physique and health types according to relative closeness and preferred sequence. The invention can better evaluate the physical health of college students.

Description

Self-adaptive evaluation method for constitutional health groups of college students
Technical Field
The invention relates to the technical field of physical health assessment, in particular to a self-adaptive assessment method for physical health groups of college students.
Background
Physique refers to the ability of a body to be able to enjoy leisure and to cope with unforeseen emergencies while being competent in daily life. The college student population is the middle-strength of future social development, the physical health of the college student population is closely related to national nationality decline and social development, and in recent years, the sports course reform work of colleges and universities plays a key role in improving the physical health of the college student. However, the sports courses at the present stage cannot fully bring the students to final education, most of the students lack the physical health consciousness, the chance and time for actively participating in physical exercise are insufficient, and even the diseases such as obesity and fatty liver are very common. For contemporary students, their physical health conditions determine not only their own quality of life, but also the inheritance and development of the future cause of the country. Therefore, the scientific evaluation of the physical health conditions of the college students and the adoption of corresponding targeted measures according to the evaluation results have great significance.
Disclosure of Invention
The invention provides a self-adaptive assessment method for the constitutional health groups of college students, which can overcome certain defects in the prior art.
The self-adaptive assessment method for the constitutional health groups of the college students is characterized by comprising the following steps: the method comprises the following steps:
1) determining a final weight by using the least square aggregation subjective and objective weights;
2) and evaluating the health weighted TOPSIS of the constitution of the university students based on the comprehensive index representation.
Preferably, the step 1) specifically comprises the following steps:
1.1) calculating subjective weight of evaluation attribute based on AHP;
1.2) calculating an evaluation attribute objective weight based on CRITIC;
1.3) calculating the synthetic weight based on least squares clustering.
Preferably, the step 1.1) specifically comprises the following steps:
1.11) constructing a judgment matrix A;
1.12) calculating index weight;
solving the maximum eigenvalue and eigenvector of the judgment matrix A by using a sum-product method, normalizing the judgment matrix A according to columns, and adding the maximum eigenvalue and eigenvector according to rows to obtain a sum vector:
Figure BDA0003357249680000021
Figure BDA0003357249680000022
aijto determine the specific values of the indices in the matrix,
Figure BDA0003357249680000023
is a pair ofijCarrying out normalization processing;
averaging the judgment matrix A to obtain a weight vector
Figure BDA0003357249680000024
Figure BDA0003357249680000025
Calculating the maximum eigenvalue lambda of the judgment matrix Amax：
Figure BDA0003357249680000026
1.13) consistency check;
after the judgment matrix eigenvector and the maximum eigenvalue are solved, consistency check needs to be carried out on the reasonability of the weight, and indexes adopted by the consistency check are as follows:
Figure BDA0003357249680000027
as long as:
Figure BDA0003357249680000031
namely, the judgment matrix is considered to have satisfactory consistency, wherein C.R. is an average random consistency index.
Preferably, the step 1.2) specifically comprises the following steps:
1.21) data normalization;
setting an evaluation system to have n evaluation objects and m evaluation indexes, firstly, distinguishing the positive and negative indexes, wherein the larger the positive index value is, the better the negative index value is, the better the positive index value is; because the measurement units of all indexes are not uniform, the indexes are standardized;
the forward direction index is as follows:
Figure BDA0003357249680000032
xijrepresenting the size of the original index value;
negative direction index:
Figure BDA0003357249680000033
1.22) calculating contrast intensity;
Figure BDA0003357249680000034
in the formula, VjIs the coefficient of variation, σ, of the j-th indexjIs the standard deviation of the j indices,
Figure BDA0003357249680000038
is the average of the j-th index;
1.23) calculating a correlation coefficient and a conflict quantization index value;
correlation coefficient r between i-th index and j-th indexijComprises the following steps:
Figure BDA0003357249680000035
in the formula, xhiAnd xhjIs the value of the ith index and the jth index of the h evaluation objects,
Figure BDA0003357249680000036
and
Figure BDA0003357249680000037
is the ith index and the jth index of the n objectsThe mean value of the index;
the conflicting quantized value index values of the jth index and other indexes are:
Figure BDA0003357249680000041
1.24) calculating the index information quantity;
the objective weight of the index is measured by contrast strength and conflict, and C is setjC represents the amount of information contained in the jth evaluation indexjCan be expressed as:
Figure BDA0003357249680000042
1.25) calculating index weight;
Figure BDA0003357249680000043
in the formula, CjThe larger the information amount contained in the jth evaluation index, the greater the relative importance of the index, i.e., the greater the weight.
Preferably, in step 1.3), the specific method is as follows:
establishing a least square comprehensive weight model:
Figure BDA0003357249680000044
the weight of each decision index is obtained from equation (14)
Figure BDA0003357249680000045
Preferably, the step 2) specifically comprises the following steps:
2.1) establishing a decision matrix;
set index set of physical health evaluation factors of college studentsIs, A ═ aij)m×nIn the formula aijRepresents the jth individual quality and health evaluation risk index of the ith student, i is 1,2, …, m, j is 1,2, …, n; wherein m is the number of students in the university for the evaluation of the biological health, and n is the number of indexes for the evaluation of the biological health of college students;
index b for evaluating health of college studentsijNormalized into a health superior type and a health inferior type;
the health excellent type indexes are as follows:
Figure BDA0003357249680000051
the health difference index is as follows:
Figure BDA0003357249680000052
2.2) constructing a weighted decision matrix;
the integrated weight f ═ determined according to the least square method (f)1,f2,…fn) Let the weighted normalized decision matrix Z ═ Zij)m×nI 1,2, …, m, j 1,2, …, n, where the elements Z in the matrix Z areijIs Zij＝fjbij；
Figure BDA0003357249680000053
2.3) determining a positive ideal solution and a negative ideal solution;
determining positive and negative ideal solutions Z+And Z-Wherein the positive ideal solution is
Figure BDA0003357249680000054
The negative ideal solution is
Figure BDA0003357249680000055
The specific calculation process is as follows:
Figure BDA0003357249680000056
Figure BDA0003357249680000057
in the above formula J1，J2Respectively as a health excellent type index and a health poor type index;
2.4) calculating the distance;
respectively calculating the physical health status of each college student to reach the positive ideal point
Figure BDA0003357249680000058
And negative ideal point
Figure BDA0003357249680000059
Figure BDA00033572496800000510
Figure BDA00033572496800000511
2.5) relative closeness and preference order;
calculating the relative closeness C of the physical health and the ideal health of each college student as shown in the formula (23)iFor the calculated relative closeness CiSorting by size, according to the judgment standard, if CiThe bigger the size is, the better the physique health of the college students is;
Figure BDA0003357249680000061
2.6) judging the physical health type;
relative closeness to constitutional health and ideal health of college students CiCarrying out normalization processing, wherein the calculation process is as shown in formula (24):
Figure BDA0003357249680000062
Figure BDA0003357249680000063
the university students' physical health is then classified according to equation (25).
The method is based on the existing national student physical health standard, starts from three aspects of physical form, physical function and physical texture, firstly screens physical health assessment indexes of college students, secondly determines index attribute weight based on least-two-times aggregation subjective and objective weight, and finally performs population self-adaptive classification assessment of physical health conditions by combining a TOPSIS method. The method has high reliability, strong operability and intuitive evaluation result, and provides a new idea for multidimensional multi-index evaluation based on the national student physical health standard and physical health management of colleges and universities.
Drawings
FIG. 1 is a flowchart of an adaptive evaluation method for the physical and health groups of college students in example 1;
FIG. 2 is a schematic diagram showing the results of classification of physical health of college students to be assessed in example 2;
FIG. 3 is a normal probability chart of the results of the adaptive evaluation of the 28 college student physical health groups in example 2.
Detailed Description
For a further understanding of the invention, reference should be made to the following detailed description taken in conjunction with the accompanying drawings and examples. It should be understood that the examples are illustrative of the invention only and not limiting.
Example 1
1 construction of index for evaluating physical health of college students
1.1 preliminary selection of index
The existing national student physical health standard refers to the national student physical health standard published by the education department of 2017. The standard is an important component of a national student development core literacy system and a academic quality standard, is an individual evaluation standard of student physical health, comprehensively evaluates the physical health level of students from three aspects of physical form, physical function and physical quality, and is shown in table 1 as an university student physical health evaluation index system constructed by primary selection.
The physical form is the material basis of human life activities, and changes with the age and the influence of factors such as environment, nutrition, diseases and the like. The physical form index is also one of the important indexes for judging the health standard of college students, and mainly comprises Body Mass Index (BMI), basal metabolic Rate (RMB), body fat rate (BFP), muscle mass rate, body water rate, inorganic salt rate, protein rate and the like.
The physical function refers to the life activities of the whole body and the organ systems composed of the body, and the physical function indexes mainly include heart rate, blood pressure, cardiovascular function index, exercise intensity measurement and respiratory function measurement[30]. In consideration of stability, the basal heart rate (morning pulse) is preferred as the heart rate index, the krampton measurement method is selected in consideration of the blood pressure measurement reliability, and the cardiovascular function index is the composite heart rate of 30 squats in 30 seconds (K ═ P)1+P2+P3-200)/10, wherein P1Is a quiet heart rate, P2Is the instantaneous heart rate after exercise, P3Is the heart rate after one minute of rest), the exercise intensity measurement is characterized by the Karsen formula (highest heart rate (220-age) -resting heart rate before exercise)/2 + heart rate before exercise), the respiratory function measurement is characterized by the size of the vital capacity.
The physical quality refers to the functions of speed, strength, endurance, sensitivity, flexibility and the like of a human body in activities, and the physical quality index is one of important bases for judging the physical health degree of college students. The speed measurement mainly comprises displacement speed (30 m running), action speed (quick knocking of two hands) and reaction speed (time measuring ruler). The strength index evaluation mainly comprises muscle strength, muscle endurance and explosive force, the muscle strength measurement adopts isometric static measurement methods (grip strength and back strength), the muscle endurance measurement adopts abdomen endurance, back endurance and double-arm endurance, and the explosive force measurement mainly adopts leg forward measurement, leg upward measurement and waist upward measurement. The endurance index measurement is divided into general endurance, speed endurance, force endurance and static endurance. The measurement of the sensitive indexes is generally carried out through the capability of changing directions in rapid movement, and methods such as 4 multiplied by 10m back and forth running, 10 seconds standing and lying support, quadrant jumping and the like are generally selected. The flexibility index usually selects joint mobility (ROM) to represent the flexibility of the body, and mainly comprises shoulder joint flexibility (shoulder rotation experiment) and spinal extension capability (posterior body bridging).
TABLE 1 Primary selection index System for evaluation of student's physical health
Figure BDA0003357249680000081
1.2 criteria screening principle
Screening of the physical health indexes is the primary task of physical health evaluation of college students and is a key link for accurately evaluating the physical health conditions of the college students. The index screening process is mainly based on the following two basic principles: firstly, screening is respectively carried out under secondary indexes of body shape, body function and body quality, and the reason is that the evaluation of the physical health of college students must be based on three aspects of body shape, body function and body quality; and secondly, the index screening is based on the correlation among indexes and the contribution degree of the indexes to an evaluation system, the indexes with larger contribution degree are reserved as key indexes, and the accumulated contribution degree reaches more than 90 percent or even higher.
1.3 index screening
The screening of the physical health indexes is a key link of the physical health evaluation of the college students, and the reasonable index screening process is the basis of the comprehensive evaluation of the physical health of the college students. The screening is completed mainly based on the correlation among indexes and the contribution degree of the indexes in the research process, and the specific screening steps are as follows.
Step.1 body morphology index screening
First, body weight, fat mass + inorganic salt mass + muscle mass, and muscle mass, protein + body water, were calculated according to the physical data measuring apparatus, and thus Body Mass Index (BMI), basal metabolic Rate (RMB), body fat rate (BFP), inorganic salt rate, and protein were preliminarily selectedThe rate is an index for evaluation of physical form. Then, 30 male college students are randomly extracted to carry out body morphology index value test, the age is extracted to be (19 +/-4) years, and the primary index variance contribution rate omega is obtained by combining principal component analysis and factor analysis methodspThe indexes with smaller contribution degrees are removed, and the specific contribution degrees of the indexes are shown in a table 2. Finally, determining the screening index, namely the constitutional fat rate A3Protein ratio A5Inorganic salt content A4Body mass index A1。
TABLE 2 results of screening for body morphology indices
Figure BDA0003357249680000091
Step.2 screening of physical Performance indicators
Firstly, randomly extracting 30 male college students (age: 19 +/-4) to carry out physical function index test; secondly, the variance contribution rate omega of each primary index is obtained by combining principal component analysis and factor analysis methodpThe indexes with smaller contribution degrees are removed, and the specific contribution degrees of the indexes are shown in table 3. Finally, a selection index, i.e. the kinetic intensity index B, is determined4Heart rate B1Cardiovascular function index B3Diastolic blood pressure B21Systolic pressure B22。
TABLE 3 screening results of physical function index
Figure BDA0003357249680000092
Step.3 screening of physical quality index
Firstly, randomly selecting 30 male college students (age is 19 +/-4 years old, height is 175 +/-5 cm) to carry out physical fitness index test; secondly, the principle that the evaluation main element needs to be covered completely is adopted, and the variance contribution rate omega of each primary index is obtained by combining the main component analysis and the factor analysis methodpThe index with the smaller rejection contribution degree is the specific contribution degree of each element index in the strength index as shown in table 4.
TABLE 4 screening results of physical fitness index
Figure BDA0003357249680000101
In conclusion, 3 factors of the physical form, the physical function and the physical quality of the college students are comprehensively considered when the college student physical evaluation index system is screened. Therefore, 16 indexes representing 3 aspects of body shape, body function and physical quality are selected to form a university student physical health evaluation index system (Table 5).
TABLE 5 index system for evaluating constitution of college students
Figure BDA0003357249680000102
As shown in fig. 1, the present embodiment provides a self-adaptive assessment method for the physical and health groups of college students, which includes the following steps:
1) determining a final weight by using the least square aggregation subjective and objective weights;
2) and evaluating the health weighted TOPSIS of the constitution of the university students based on the comprehensive index representation.
The step 1) specifically comprises the following steps:
1.1) calculating subjective weight of evaluation attribute based on AHP;
the AHP is thought to establish a hierarchical structure describing system functions or characteristics according to the problem requirements, and form a judgment matrix of upper-layer factors to lower-layer factors through the relative importance of two comparative factors to provide a sequence formed by the relative importance degree of the lower-layer related factors to the upper-layer factors. The method respectively determines relative importance sequences of three aspects of body shape, body function and body quality to the evaluation of the physical health of college students by using a hierarchical analysis method; the importance sequence of Body Mass Index (BMI), basal metabolic Rate (RMB), body fat rate (BFP), muscle rate, body water rate to body morphology; the importance sequence of heart rate, blood pressure, cardiovascular function index, exercise intensity index, respiratory function index to body function; the influence of speed, strength, endurance, sensitivity, flexibility on physical fitness. The specific steps of calculating the index weight by the analytic hierarchy process are as follows:
1.11) constructing a judgment matrix A; the experts were invited to compare the importance of all the indicators of the university for the biological health, as per the definition of importance table (see table 5), as in table 6.
TABLE 5 Scale importance definition Table
Figure BDA0003357249680000111
TABLE 6 comparison of importance
Figure BDA0003357249680000112
1.12) calculating index weight;
solving the maximum eigenvalue and eigenvector of the judgment matrix A by using a sum-product method, normalizing the judgment matrix A according to columns, and adding the maximum eigenvalue and eigenvector according to rows to obtain a sum vector:
Figure BDA0003357249680000113
Figure BDA0003357249680000121
aijto determine the specific values of the indices in the matrix,
Figure BDA0003357249680000122
is a pair ofijCarrying out normalization processing;
averaging the judgment matrix A to obtain a weight vector
Figure BDA0003357249680000123
Figure BDA0003357249680000124
Calculating the maximum eigenvalue lambda of the judgment matrix Amax：
Figure BDA0003357249680000125
1.13) consistency check;
after the judgment matrix eigenvector and the maximum eigenvalue are solved, consistency check needs to be carried out on the reasonability of the weight, and indexes adopted by the consistency check are as follows:
Figure BDA0003357249680000126
as long as:
Figure BDA0003357249680000127
i.e. the decision matrix is considered to have a satisfactory consistency, where c.r. is an average random consistency index, and the values are shown in table 7.
TABLE 7 average random consistency index
Figure BDA0003357249680000128
1.2) calculating an evaluation attribute objective weight based on CRITIC;
the CRITIC method is an objective weighting method for calculating weights according to importance criteria of relevance among hierarchies. The method determines index weight on the basis of the conflict between contrast strength and indexes, wherein the contrast strength generally takes a data standard deviation, and a variation coefficient is taken as the contrast strength in consideration of the influence of a mean value on the contrast strength; the conflict between the indicators is based on the correlation between the indicators, and high correlation indicates low conflict.
In the step 1.2), the method specifically comprises the following steps:
1.21) data normalization;
setting an evaluation system to have n evaluation objects and m evaluation indexes, firstly, distinguishing the positive and negative indexes, wherein the larger the positive index value is, the better the negative index value is, the better the positive index value is; because the measurement units of all indexes are not uniform, the indexes are standardized;
the forward direction index is as follows:
Figure BDA0003357249680000131
negative direction index:
Figure BDA0003357249680000132
1.22) calculating contrast intensity;
Figure BDA0003357249680000133
in the formula, VjIs the coefficient of variation, σ, of the j-th indexjIs the standard deviation of the j indices,
Figure BDA0003357249680000134
is the average of the j-th index;
1.23) calculating a correlation coefficient and a conflict quantization index value;
correlation coefficient r between i-th index and j-th indexijComprises the following steps:
Figure BDA0003357249680000135
in the formula, xhiAnd xhjIs the value of the ith index and the jth index of the h evaluation objects,
Figure BDA0003357249680000136
and
Figure BDA0003357249680000137
is the mean of the ith index and the jth index in the n objects;
the conflicting quantized value index values of the jth index and other indexes are:
Figure BDA0003357249680000138
1.24) calculating the index information quantity;
the objective weight of the index is measured by contrast strength and conflict, and C is setjC represents the amount of information contained in the jth evaluation indexjCan be expressed as:
Figure BDA0003357249680000141
1.25) calculating index weight;
Figure BDA0003357249680000142
in the formula, CjThe larger the information amount contained in the jth evaluation index, the greater the relative importance of the index, i.e., the greater the weight.
1.3) calculating the synthetic weight based on least squares clustering.
In the step 1.3), the specific method comprises the following steps:
establishing a least square comprehensive weight model
Figure BDA0003357249680000143
The weight of each decision index is obtained from equation (14)
Figure BDA0003357249680000144
In the step 2), the method specifically comprises the following steps:
2.1) establishing a decision matrix;
the TOPSIS method is a simple and efficient multi-target decision analysis method, and the basic principle is to optimally sort projects by calculating the relative distance between an index vector and a positive ideal solution and a negative ideal solution of an evaluation object. Considering the dimension difference between different university student physical health index factors, before the university student physical health evaluation, the university student physical health needs to be uniformly subjected to dimensionless treatment. Let the index set of constitutional health evaluation factors of college students be (a ═ a)ij)m×nIn the formula aijRepresents the jth individual quality and health evaluation risk index of the ith student, i is 1,2, …, m, j is 1,2, …, n; wherein m is the number of students in college student physical health evaluation, and n is the number of indexes in college biological health evaluation.
Index b for evaluating health of college studentsijNormalized into a health superior type and a health inferior type;
the health excellent type indexes are as follows:
Figure BDA0003357249680000151
the health difference index is as follows:
Figure BDA0003357249680000152
2.2) constructing a weighted decision matrix;
the integrated weight f ═ determined according to the least square method (f)1,f2,…fn) Let the weighted normalized decision matrix Z ═ Zij)m×nI 1,2, …, m, j 1,2, …, n, where the elements Z in the matrix Z areijIs Zij＝fjbij；
Figure BDA0003357249680000153
2.3) determining a positive ideal solution and a negative ideal solution;
determining positive and negative ideal solutions Z+And Z-Wherein the positive ideal solution is
Figure BDA0003357249680000154
The negative ideal solution is
Figure BDA0003357249680000155
The specific calculation process is as follows:
Figure BDA0003357249680000156
Figure BDA0003357249680000157
in the above formula J1，J2Respectively as a health excellent type index and a health poor type index;
2.4) calculating the distance;
respectively calculating the physical health status of each college student to reach the positive ideal point
Figure BDA0003357249680000158
And negative ideal point
Figure BDA0003357249680000159
Figure BDA00033572496800001510
Figure BDA00033572496800001511
2.5) relative closeness and preference order;
calculating the relative closeness C of the physical health and the ideal health of each college student as shown in the formula (23)iFor the calculated relative closeness CiSorting by size, according to the judgment standard, if CiThe larger theThe better the physical health of the college students;
Figure BDA0003357249680000161
2.6) judging the physical health type;
relative closeness to constitutional health and ideal health of college students CiCarrying out normalization treatment, wherein the calculation process is as shown in a formula (24);
Figure BDA0003357249680000162
Figure BDA0003357249680000163
the university students' physical health is then classified according to equation (25).
Example 2
3.1 index weight determination
3.1.1 subjective weight determination
And (3) determining the weight of the evaluation factor by adopting an analytic hierarchy process according to the established university student system health evaluation index system, wherein the specific process is shown in the formulas (1) to (6). A judgment matrix of a target layer to a criterion layer is constructed through expert judgment, scoring and the like, and is recorded as:
Figure BDA0003357249680000164
according to the weight of each evaluation index, the characteristic value lambda can be obtainedmax＝3.000,C.I.＝0,C.R.＝ 0.58,
Figure BDA0003357249680000165
Therefore, the judgment matrix has good consistency, and the total index weight matrix
Figure BDA0003357249680000166
It is acceptable.
Similarly, the index weights of the index layers are normalized according to the variance contribution degrees, the variance contribution degrees of the indexes of the index layers are shown in tables 2-4, and the result of the subjective method weight calculation of the total index layer and the index layer is shown in table 8.
TABLE 8 subjective method weight calculation results
Figure BDA0003357249680000171
3.1.2 Objective weight determination
The objective weight determination is performed based on the CRITIC method (equations (7) to (13)), and 28 samples are selected during the research process to perform objective weight calculation (see table 9), and the specific calculation result is shown in table 10.
TABLE 9 basic information Table of test sample
Figure BDA0003357249680000172
TABLE 10 Objective weight-related parameter results Table
Figure BDA0003357249680000173
Figure BDA0003357249680000181
3.1.3 determination of least squares synthetic weights
According to the formulas (14) - (15), the least square fitting is carried out on the subjective weight and the objective weight, the fitting equation is shown in table 11, the minimum linear fitting residual error and the best effect are found according to the fitting equation, the subjective weight and the objective weight have better consistency, the exponential fitting, logarithmic fitting and power exponential fitting effects are the second order, the fitting effects of polynomials of the second order and above are poor, and the effects are poor along with the increase of the polynomial times. Therefore, the linear fitting result is selected as the fitting function to calculate the comprehensive weight, and the result is normalized, and the final calculation result is shown in the following table 12. According to the least square method fitting result, the subjective weight and the objective weight have good consistency, and meanwhile, the linear fitting effect is optimal.
TABLE 11 least squares fitting equation
Figure BDA0003357249680000182
TABLE 12 least squares clustering weight table
Figure BDA0003357249680000183
3.2 university student physical health TOPSIS evaluation
According to the established TOPSIS method undergraduate physique health evaluation optimization model, the student samples are evaluated and optimized, and the specific calculation process is as follows:
1) and (5) establishing an optimal decision matrix for the physical health evaluation of the college students according to the decision matrix establishing equations (16) to (17), and meanwhile, carrying out standardized processing.
2) Obtaining a weighted decision matrix Z by calculation according to a formula (18)ij。
3) Determining a positive ideal solution Z according to equations (19) - (20)+Negative ideal solution Z-。
Z+＝(0.0303,0.0241,0.0256,0.0297,0.0313,0.0293,0.0251,0.0286,0.0294, 0.0197,0.0223,0.0212,0.0208,0.0226)
Z-＝(0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000, 0.0000,0.0024,0.0000,0.0000,0.0000)
4) The closeness between the physical health of each university student and the ideal health is calculated according to the formulas (21) to (23), and normalization processing is performed (table 13).
TABLE 13 distance values and closeness of students
Figure BDA0003357249680000191
5) The university students to be evaluated are classified into physical health categories according to the formulas (24) to (25), and the results of the physical health categories of the university students to be evaluated are shown in fig. 2.
3.3 assessment results normality test
The normal state test methods commonly used include a normal probability paper method, a Charcot-Wilktest (Shapiro-Wilktest), a Kolmogorov test method, and a skewness-kurtosis test method. As shown in fig. 3, a normal probability chart of the results of the 28 college student physical health evaluations shows that the normal probability chart is substantially close to a straight line, which indicates that the reliability of the evaluation results is high and the model evaluation results are objective. In addition, the curve fluctuates due to the small sample size (28 college students), which is a normal phenomenon, and when the sample size is large enough, the distribution is closer to a straight line.
Discussion and analysis
The evaluation of the physical health of college students based on the national student physical health standards is a key link for ensuring that the biological health of college students meets the national basic requirements, and the embodiment provides a self-adaptive assessment method of the physical health population of college students based on the least square method for aggregating subjective and objective weights (AHP & CRITIC) and the TOPSIS method. In view of the fact that the subjectivity of index weight is not considered in the traditional method, firstly, evaluation index primary selection is carried out on the basis of 'national and academic biological matter health standards', and index screening is carried out according to principal component analysis and index contribution degree, so that a final evaluation index system is determined; secondly, determining subjective weight and objective weight of the index based on an Analytic Hierarchy Process (AHP) and a CRITIC method, and determining a clustering weight based on least square on the basis of judging that the subjective weight and the objective weight have better consistency; and finally, performing population adaptive comprehensive evaluation on the physical health of the college students based on the improved TOPSIS method and the clustering weight. Example analysis and result analysis show that the embodiment has high reliability, strong operability and intuitive evaluation result, and provides a new idea for the physical health management of college students for multi-dimensional multi-index evaluation based on the national student physical health standard.
The present invention and its embodiments have been described above schematically, and the description is not intended to be limiting, and what is shown in the drawings is only one embodiment of the present invention, and the actual structure is not limited thereto. Therefore, if the person skilled in the art receives the teaching, without departing from the spirit of the invention, the person skilled in the art shall not inventively design the similar structural modes and embodiments to the technical solution, but shall fall within the scope of the invention.

Claims (6)

1. The self-adaptive assessment method for the constitutional health groups of the college students is characterized by comprising the following steps: the method comprises the following steps:
1) determining a final weight by using the least square aggregation subjective and objective weights;
2) and evaluating the health weighted TOPSIS of the constitution of the university students based on the comprehensive index representation.
2. The college student physical health population adaptive assessment method according to claim 1, wherein: the step 1) specifically comprises the following steps:
1.1) calculating subjective weight of evaluation attribute based on AHP;
1.2) calculating an evaluation attribute objective weight based on CRITIC;
1.3) calculating the synthetic weight based on least squares clustering.
3. The college student physical health population adaptive evaluation method according to claim 2, wherein: in the step 1.1), the method specifically comprises the following steps:
1.11) constructing a judgment matrix A;
1.12) calculating index weight;
solving the maximum eigenvalue and eigenvector of the judgment matrix A by using a sum-product method, normalizing the judgment matrix A according to columns, and adding the maximum eigenvalue and eigenvector according to rows to obtain a sum vector:
Figure FDA0003357249670000011
Figure FDA0003357249670000012
aijto determine the specific values of the indices in the matrix,
Figure FDA0003357249670000013
is a pair ofijCarrying out normalization processing;
averaging the judgment matrix A to obtain a weight vector
Figure FDA0003357249670000014
Figure FDA0003357249670000015
Calculating the maximum eigenvalue lambda of the judgment matrix Amax：
Figure FDA0003357249670000016
1.13) consistency check;
after the judgment matrix eigenvector and the maximum eigenvalue are solved, consistency check needs to be carried out on the reasonability of the weight, and indexes adopted by the consistency check are as follows:
Figure FDA0003357249670000021
as long as:
Figure FDA0003357249670000022
namely, the judgment matrix is considered to have satisfactory consistency, wherein C.R. is an average random consistency index.
4. The college student physical health population adaptive evaluation method according to claim 3, wherein: in the step 1.2), the method specifically comprises the following steps:
1.21) data normalization;
setting an evaluation system with n evaluation objects and m evaluation indexes, firstly, distinguishing the positive and negative indexes, wherein the larger the positive index value is, the better the negative index value is; because the measurement units of all indexes are not uniform, the indexes are standardized firstly;
the forward direction index is as follows:
Figure FDA0003357249670000023
xijrepresenting the size of the original index value;
negative direction index:
Figure FDA0003357249670000024
1.22) calculating contrast intensity;
Figure FDA0003357249670000025
in the formula, VjIs the coefficient of variation, σ, of the j-th indexjIs the standard deviation of the j indices,
Figure FDA0003357249670000026
is the average of the j-th index;
1.23) calculating a correlation coefficient and a conflict quantization index value;
correlation coefficient r between i-th index and j-th indexijComprises the following steps:
Figure FDA0003357249670000031
in the formula, xhiAnd xhjIs the value of the ith index and the jth index of the h evaluation objects,
Figure FDA0003357249670000032
and
Figure FDA0003357249670000033
is the mean of the ith index and the jth index in the n objects;
the conflicting quantized value index values of the jth index and other indexes are:
Figure FDA0003357249670000034
1.24) calculating the index information quantity;
the objective weight of the index is measured by contrast strength and conflict, and C is setjC represents the amount of information contained in the jth evaluation indexjCan be expressed as:
Figure FDA0003357249670000035
1.25) calculating index weight;
Figure FDA0003357249670000036
in the formula, CjThe larger the information amount contained in the jth evaluation index, the greater the relative importance of the index, i.e., the greater the weight.
5. The college student physical health population adaptive assessment method according to claim 4, wherein: in the step 1.3), the specific method comprises the following steps:
establishing a least square comprehensive weight model:
Figure FDA0003357249670000037
the weight of each decision index is obtained from equation (14)
Figure FDA0003357249670000041
6. The college student physical health population adaptive evaluation method according to claim 5, wherein: in the step 2), the method specifically comprises the following steps:
2.1) establishing a decision matrix;
the index set of the constitutional health evaluation factors of college students is that A is (a)ij)m×nIn the formula aijRepresents the jth individual quality and health evaluation risk index of the ith student, i is 1,2, …, m, j is 1,2, …, n; wherein m is the number of students in the university student's physical health assessment, and n is the number of indexes in the university student's physical health assessment;
index b for evaluating health of college studentsijNormalized into a health superior type and a health inferior type;
the health excellent type indexes are as follows:
Figure FDA0003357249670000042
the health difference index is as follows:
Figure FDA0003357249670000043
2.2) constructing a weighted decision matrix;
the integrated weight f ═ determined according to the least square method (f)1,f2,…fn) Let the weighted normalized decision matrix Z ═ Zij)m×n，i＝1,2,…,m,j＝1,2, …, n, wherein the element Z in the matrix ZijIs Zij＝fjbij；
Figure FDA0003357249670000044
2.3) determining a positive ideal solution and a negative ideal solution;
determining positive and negative ideal solutions Z+And Z-Wherein the positive ideal solution is
Figure FDA0003357249670000045
The negative ideal solution is
Figure FDA0003357249670000046
The specific calculation process is as follows:
Figure FDA0003357249670000047
Figure FDA0003357249670000048
in the above formula J1，J2Respectively as a health excellent type index and a health poor type index;
2.4) calculating the distance;
respectively calculating the physical health status of each college student to reach the positive ideal point
Figure FDA0003357249670000051
And negative ideal point
Figure FDA0003357249670000052
Figure FDA0003357249670000053
Figure FDA0003357249670000054
2.5) relative closeness and preference order;
calculating the relative closeness C of the physical health and the ideal health of each college student as shown in the formula (23)iFor the calculated relative closeness CiSorting by size, according to the judgment standard, if CiThe bigger the size is, the better the physique health of the college students is;
Figure FDA0003357249670000055
2.6) judging the physical health type;
relative closeness to constitutional health and ideal health of college students CiCarrying out normalization processing, wherein the calculation process is as shown in formula (24):
Figure FDA0003357249670000056
Figure FDA0003357249670000057
the university students' physical health is then classified according to equation (25).
CN202111356260.9A 2021-11-16 2021-11-16 Self-adaptive evaluation method for constitutional health groups of college students Pending CN114242241A (en)

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