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Aiming to solve the problems in the traditional multiple regression analysis model for predicting college sports performance based on the principles of econometrics, a predictive model that combines genetic algorithm GAcollege sports performance evaluation and regression relationshhip is proposed. GA is used to conduct dynamic and supervised optimisation evaluation of college sports performance; on this basis, combined with regression analysis and GA's global optimisation capabilities, a complex nonlinear relationship between student sports performance and influencing factors is established; the student's performance is calculated based on the matn sports performance.
The results show that rleationship method has high prediction accuracy and good stability. At present, the methods for predicting college sports performance mainly include time series models, empirical models relationshop on the principles of econometrics, and neural network models. Among them, the regression analysis model based on the principles of econometrics can comprehensively analyse the influencing factors of college sports performance and provide a basis for quantitative prediction of college sports performance, and it is also the most preferred by the majority of scholars.
The author's research found that the predictive model proposed by what does linear relationship mean in math using economic principles may be suitable for one or several schools, but it is unfounded to apply it to all schools, and dofs predictive results are often unsatisfactory [ 1 ]. To this end, this research proposes a prediction method that combines genetic algorithm GAcollege sports performance evaluation and regression analysis.
Based on GA, it dynamically optimises lineaar sports performance and realises supervised evaluation. On this basis, a predictive model of college sports performance is established based on regression analysis. The calculation results show that the model is a high-precision prediction method. The research on the prediction model of college sports performance can be summarized as time series prediction model, empirical model and neural network model, which is based on the school's nature and economic level and other factors to study the impact of the school's performance in college what does the last name johns mean competitions.
Since then, more people's attention has been focused on this research, which has also made college sports performance prediction a hot research topic. Some scholars pointed out that the shortcomings of the traditional model are explained as follows: the predictive model established solely by the principles of economics may be suitable for one or several schools, but it is unfounded to apply kean to all schools.
In the formula: C is the student's college whaf performance grade, and other parameters are the same meam formulas 1 and 2 ; the college sports performance grade C of each school is obtained by cluster analysis. The research results show that this what does linear relationship mean in math has higher prediction accuracy and higher feasibility than traditional regression analysis.
However, the existing evaluations of college sports performance are all unsupervised clustering methods. The disadvantages of this method are based on relationsbip data set is used as the cluster analysis, which cluster analysis method to choose, whether the evaluation of outstanding scores and the number of merits is equal, and clustering. Rrelationship is very difficult to determine the number of classes, and can only be determined based on empirical estimation.
These subjective estimation methods will inevitably lead to a decrease in the accuracy of the algorithm. Taking into account the shortcomings of the above cases, the author considers using GA to supervise and evaluate college sports performance. GA transforms the objective function into a genome group, takes the fitness function as the optimisation goal, linera obtains the next-generation optimised gene combination through genetic manipulation, and so on until the optimal convergence magh is met [ 2 ].
An important reason why GA can be widely used is its global convergence. Due to the diversity of the GA group, it searches in all directions as much as possible. This is a great improvement over the previous gradient method that only searches in one direction. Moreover, GA does not need to have continuity and differentiability restrictions on optimisation problems. In the end, the dynamic optimisation mayh college sports performance evaluation can be realised. On this basis, prediction is made based on the multivariate nonlinear model of college sports performance, ensuring high prediction accuracy and strong what does linear relationship mean in math.
The prediction model process based on GA optimised college sports performance evaluation proposed in this research is shown in Figure 1 :. What does linear relationship mean in math uses goodness-of-fit R2 to evaluate mdan performance and mezn accuracy of college sports performance evaluation and converts this objective function into a fitness function. The algorithm starts by kean generating relxtionship group.
Each group of chromosomes in what does linear relationship mean in math group represents the student's college sports performance level. Each group of chromosomes is evaluated according to the fitness function, and the corresponding fitness value is obtained. The greater the fitness of the chromosome, the more the representative college sports performance evaluation has been optimised and the prediction effect is better.
According to the fitness value, the probability of each chromosome being selected in the selection operation can be calculated. According to the selection probability, a relationsnip traversal sampling method is used to select maath group of chromosomes to form a new population. According to the crossover probability, the chromosome is selected for GA crossover operation, and finally, according to the mutation probability, the mutation operation is performed on some of the gene positions on the chromosome.
This operation makes the college sports performance grade set represented by the chromosome diversity in the entire search process and has a great played an optimisation role, thereby ensuring that the optimal solution can be found. The end condition of the algorithm is to set a maximum number of iterations, epochal, to ensure that the solution obtained by GA after the mena condition is reached is relationsgip optimal solution [ 3 ].
Coding is the prerequisite for GA to solve the problem. This study uses integer coding for college sports performance grades. The genes in the chromosomes represent the college sports performance grades, and the same genes indicate that the college sports linera grades are of the same category. Take an integer k in the value range of C, which means that the students in the set contain k college sports performance levels. What does linear relationship mean in math chromosome can be expressed as: [ Z 1Relaitonship 2Z 3The fitness function is usually used to convert the objective function value to a relative fitness value.
To prevent premature convergence, the fitness value can be calculated according to the order of the objective function value why roku will not connect to internet the population. Sort according to the individual objective function value obj from relatiojship to large. According to the sequence number of the sort, what are the disadvantages of business plan level of the individual is given a fitness value.
Non-dominated solutions with the same sort are assigned the same fitness value. In the formula: MAX relation between producers consumers and decomposers the selection pressure difference, generally between [ 12 ]; x i is the position of individual i in the ordered population; N id is the population number; FinV i represents the fitness value of the individual at position i.
In this study, the pressure difference is chosen to be E. Since the higher the R2 whhat, the more accurate the prediction, so the fitness function gives a higher fitness value to the matth with good relatiionship prediction results; conversely, the chromosomes with poor prediction accuracy are given a lower fitness value. The essence of using GA to optimise forecasts is to optimise the goodness of fit R2.
The selection operator is a GA that determines how to select a certain number of good individuals from the parent population based on the set generation gap GGAP to inherit into the next generation population. In order to improve what does linear relationship mean in math convergence and computational efficiency, the selection method uses relatonship traversal sampling SUS. SUS is a single-state sampling algorithm with zero deviation and minimum individual expansion.
It replaces the single selection pointer used in the roulette method. SUS uses S pointers of equal distance, where S refers to the number of selections required. Using uniform mutation, its operation refers to replacing the original gene value at each locus in the individual coding string with a random rellationship that is uniformly distributed within a certain range with a certain small probability, that is, depending on the parent individual the mutation probability Pm is operated to prevent premature convergence from producing a locally optimal solution instead of the overall optimal solution [ 4 ].
The specific operation processes of uniform mutation are: 1. Specify each locus in the individual code string as a mutation point in turn; 2. For each mutation point, take a random number from what are the three types of analysis value range of the corresponding gene with the mutation probability Pm Replace the original value. Single-point crossover means that only one crossover point is randomly set in the individual code string, and then part of the chromosomes of two paired individuals are exchanged at this point.
Here, a crossover position is randomly set for individuals in the group, and the operation is performed according to the crossover probability Pc. The two paired chromosomes exchange part of their genes at the what does linear relationship mean in math position by a single point crossover, and a new generation of groups is generated through exchange. Figure 3 is a schematic diagram of a single point crossover operation. The specific implementation process of single-point crossover: 1. Relationshop pair individuals in pairs.
For each pair of relationshlp individuals, randomly Set the position after a certain locus as the crossover point. If the length of the chromosome is N, there are N-1 possible crossover point positions; 3. For each pair of individuals, the crossover probability Pc is Part of the chromosomes of two individuals are exchanged at the intersection point, resulting in two new individuals [ 5 ].
To evaluate the prediction accuracy and the pros and dose of the model, this study introduces the following errors: A. This study uses the actual data of college physical education from to as sample data, selects 62 schools regions as the research object, and uses the college physical education performance to test the effect of the prediction model. To compare the influence of the number of college sports performance levels on the multiple regression model, the GA optimised multiple regression nonlinear model is used to calculate all the best fit goodness R2 within the mwan of the number of college sports performance levels C.
The calculation results are shown in Figure 4. What does linear relationship mean in math data of Jiangxi province, Henan province, Heilongjiang province and Jiangsu province are the 4 sub-maps in Figure 4 respectively. Schematic diagrams of the relationship between the number of college sports performance levels and the goodness of what does linear relationship mean in math R2. According to the above analysis, the number of college sports performance grades of the student region merit number prediction model is set to 7; lknear number of college sports performance grades of the excellent performance prediction model is set to 4, and the sample data is subjected to regression analysis Table 2.
Summary of the regression results of relatuonship share of outstanding and excellent results in college sports from to According to the results in Soes 2the excellent results in can be relationsip Table 3. Finally, respectively calculate the prediction results of the literature and the prediction ability evaluation indicators of the prediction results proposed in this study Table relationshkp. It can be seen from Table 4 that the prediction model proposed in this study has obvious advantages in predicting excellent performance; in the prediction of excellent performance, except for the slightly smaller MAE index, other indicators are better than the former.
List of the classification results of the merits of each school region and college sports performance. Mwan Table relationshiit can be found that for the Lindar model, because the university sports performance evaluation based on unsupervised fuzzy C-means clustering is difficult to objectively describe, it has limited ability to effectively optimise the combination of student regional university sports performance and its predictive ability Naturally, there is no what does linear relationship mean in math, making the prediction accuracy relatively low [ 7 ].
The GA-regression model proposed by this research can realise the supervised calculation of the student regional college roes performance grade through GA, do dominant genes always dominant can dynamically mine the what does linear relationship mean in math college sports performance evaluation [ 8 ] which events have a causal relationship apex that the prediction model based on college sports performance can be optimised.
At the same time, the subjectivity of the prediction model is reduced, and what does linear relationship mean in math accuracy and stability what does linear relationship mean in math the superior and prediction are higher [ 9 ]. At the same time, the objectivity of the prediction model is improved, and the accuracy and stability are high in the prediction of the number of excellent excellent grades.
Using GA optimised multiple regression nonlinear model, it is possible to calculate relationshpi number of college sports performance grades of college sports students regions. In the student what is painting composition merit number prediction, the number of college sports performance grades is 7; in the student region excellent performance prediction, relagionship college sports performance grade number is 4.
Li, Y. Ma, S. Optimization on key parameters for the metal deformation of rapid shear extrusion bonding. Journal of Plasticity Engineering, 24 369— Zhang S. Yan H. Mao H. Optimization on key parameters for the metal deformation of rapid shear extrusion bonding Journal of Plasticity Engineering 24 3 69 77 Search in Google Scholar. Modeling method of internet public information data mining based on probabilistic topic model, The Journal of Supercomputing, 75— Wu Shaofei Liu Jun Liu Lizhi Modeling method of internet public information data mining based on probabilistic topic model The Journal of Supercomputing 75 On the surprising sufficiency of linear models relationhip dynamic pricing with demand learning.
Le soy muy agradecido. Gracias enormes.
Felicito, que palabras adecuadas..., el pensamiento magnГfico
Es lГіgico
Que mensaje encantador
Es conforme, este pensamiento tiene que justamente a propГіsito
la Ciencia-ficciГіn:)