Student comprehensive activity behavior simulation method and storage medium based on extended cellular machine

Abstract

The present invention relates to a method and storage medium for simulating student comprehensive activity behaviors based on an extended cellular machine. The method simulates student comprehensive activity behaviors through a behavior simulation model based on an extended cellular machine, and comprises the following steps: S1, configuring initial parameters of the behavior simulation model; S2, calculating the cellular transition probability p i,j,z ; S3, calculate the student's final movement probability P ijz S4. Compare the current time step with the previous time step to determine whether the student's current exercise state has changed, and calculate the student's current intimacy. This method, based on an extended cellular machine model and combining characteristics of student campus activities, comprehensively analyzes different time periods such as study, rest, exams, and holidays. It also incorporates external guiding factors to analyze the spatiotemporal patterns of student exercise behavior, explore the key factors influencing student exercise behavior, ensure students' physical and mental health, and provide a basis for schools to formulate reasonable sports plans and resource allocation.

Description

Technical Field

[0001] The present invention relates to the technical field of activity behavior simulation, and in particular to a student comprehensive activity behavior simulation method based on an extended cellular machine and a storage medium. Background Art

[0002] With economic development and the advancement of the times, more and more people are realizing the importance of good physical fitness and are becoming more inclined to exercise. Therefore, it is crucial for schools to accurately assess students' physical activity status and adjust physical activity plans to balance academics and physical activity, ensuring students' overall health without compromising their academic performance and promoting their all-round development. However, the current lack of specific exercise models for school students and the lack of analysis and prediction of student exercise behavior makes it difficult for schools to develop appropriate physical activity plans and allocate resources to promote student exercise. Summary of the Invention

[0003] Based on this, it is necessary to provide a student comprehensive activity behavior simulation method and storage medium based on extended cellular machines to address the current problem of lack of sports models for school students and lack of analysis and prediction of student sports behavior, which makes it difficult for schools to formulate reasonable sports plans and resource allocation to promote student sports.

[0004] A method for simulating student comprehensive activity behaviors based on an extended cellular machine is provided, wherein the method simulates student comprehensive activity behaviors through a behavior simulation model based on an extended cellular machine; the method comprises the following steps:

[0005] S1. Initial parameter configuration of the behavior simulation model;

[0006] S2. Calculate the cell transfer probability p i,j,z , and its calculation formula is:

[0007]

[0008] Where i represents the index of the student's horizontal coordinate in the cellular space; j represents the index of the student's vertical coordinate in the cellular space; z represents the index of all the student's changeable motion features; N is the adjustment parameter; S ijz Indicates the zth motion feature of the current student; L ij Indicates the closeness between students; R ij Indicates the student's communication scope; k S ,k L ,k R are the sensitivity coefficients of movement characteristics, intimacy, and social scope respectively; E represents the environmental parameter; T H Indicates holiday time, T C Indicates time spent in school;

[0009] S3. Calculate the student's final movement probability P ijz , and its calculation formula is:

[0010] P ijz =KT u rp i,j,z

[0011] Where K represents the adjustment parameter; T u represents the ratio of available exercise time to unavailable exercise time in the time step; r represents the evolution stage of the current time step. If the evolution stage is judged to be the leisure learning period, exercise is performed with probability r = α; if the evolution stage is judged to be the regular learning period, exercise is performed with probability r = β; if the evolution stage is judged to be the key examination period, exercise is performed with probability r = γ; where α, β, and γ are all reference probabilities, and 1>α>β>γ;

[0012] S4. Compare the current time step with the previous time step to determine whether the student's current motion state has changed, and calculate the student's current intimacy; if the student's current motion state has not changed, the sensitivity coefficient k of the motion feature s remains unchanged; if the student's current motion state changes, the sensitivity coefficient k of the motion feature s Reduce Δδ; if the current intimacy is greater than or equal to the set threshold, the sensitivity coefficient k of the intimacy L Increase Δσ, and the intimacy is less than the threshold, then the sensitivity coefficient k of intimacy L Reduce Δσ;

[0013] S5, the sensitivity coefficient k of the changed motion feature s and the sensitivity coefficient k of intimacy L Substitute the next time step and repeat S2 to S5 until the simulation ends.

[0014] As a preferred example, the cell space of the behavior simulation model is 100*100, the neighborhood type is Moore type; and the space occupied by each cell is 1*1.

[0015] As a preferred example, the initial parameters include environmental parameters, student sports parameters and student status; the environmental parameters include the overall probability of students joining clubs, the overall probability of students winning awards, whether the school has sports infrastructure and the time ratio of students to and from classes; the student sports parameters include the sensitivity coefficient k of sports characteristics S , sensitivity coefficient k of intimacy L and the sensitivity coefficient k of the communication scope R The student status includes the student's gender, the student's sports type, the student's sports intensity, the student's sports time, whether the student joins a club, and whether the student has won an award.

[0016] As a preferred example, the motion feature S ijz The expression is:

[0017]

[0018] Where F is the adjustment parameter of motion characteristics; St ij is the current student sports type; St xy The sports types of other students in the current student's social circle; Sp ij is the current student exercise intensity; Sp xy Sd is the exercise intensity of other students in the current student's social circle; ij is the current student exercise time frequency; Sd xy The movement time frequency of other students in the current student's communication range; Sjc ij Whether the current student joins the club; Sjc xy Whether other students in the current student's social circle join the club; ij Whether the current student has won an award; Sr xy Whether other students in the current student's social circle have won awards; k t ,k p ,k d ,k jc ,k r St ij ,Sp ij ,Sd ij ,Sjc ij ,Sr ij Parameter coefficients of the five motion states.

[0019] As a preferred example, the intimacy L ij The expression is:

[0020]

[0021] Where, L ij Indicates the closeness between the target student and other students in the communication range; L xy Indicates the closeness of other students to the target student; G ij Indicates the gender of the target student; G xy Indicates the gender of other students at the coordinate (x, y); k ijxy Represents the weight of the special relationship; R ij Indicates the student's communication scope.

[0022] As a preferred example, the communication range R ij The expression is:

[0023]

[0024] Where Max is the maximum communication range set; L set is the average intimacy threshold set; W represents the weight of gender and bond between students, and W>1; C ij Indicates the grade of the target students; C xy Indicates the corresponding grade of other students at coordinate (x, y).

[0025] As a preferred example, in S3, the evolution stage is divided into three stages: a leisure learning period, a regular learning period and a key examination period; wherein, the leisure learning period is characterized by less class time and more rest time and after-school time; the regular learning period is characterized by an increase in class time and a gradual decrease in students' free time; the key examination period is characterized by a shortened rest time and after-school time, and a sharp decrease in students' free time.

[0026] As a preferred example, the three evolutionary stages are cyclically performed in a changing order, and the changing order is regular learning period - leisure learning period - regular learning period - key examination period.

[0027] As a preferred example, parameter evaluation is performed after simulating the comprehensive activity behavior of students; the parameter evaluation is used to explore the key factors that affect the learning activity behavior.

[0028] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the student comprehensive activity behavior simulation method as described above.

[0029] The beneficial effects of the present invention are as follows: based on the extended cellular machine model, the present invention combines the characteristics of students' campus activities, comprehensively analyzes different time periods such as learning, rest, examinations, holidays, etc., adds external guiding factors, analyzes the spatiotemporal patterns of students' exercise behavior, explores the key factors affecting students' exercise behavior, ensures students' physical and mental health, and provides a basis for schools to formulate reasonable sports plans and resource allocation. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a flow chart of the method for simulating students' comprehensive activity behaviors based on the extended cellular machine;

[0031] Figure 2 A statistical graph showing changes in different exercise intensities over time for students who chose football;

[0032] Figure 3 A statistical graph showing the duration of different sports over time for students who chose football;

[0033] Figure 4This is a statistical graph showing the changes in different exercise intensities over time for students who chose basketball;

[0034] Figure 5 A statistical graph showing the duration of different sports over time for students who chose basketball;

[0035] Figure 6 This is a statistical graph showing the changes in different exercise intensities over time for students who choose swimming;

[0036] Figure 7 A statistical graph showing the duration of different exercises over time for students who chose swimming;

[0037] Figure 8 This is a graph showing changes in students' average exercise duration;

[0038] Figure 9 This is a graph showing changes in students' average exercise intensity;

[0039] Figure 10 This is a statistical diagram of the change of motion characteristics over time under different motion characteristic sensitivity coefficients;

[0040] Figure 11 This is a statistical graph showing the change of motion characteristics over time under different intimacy sensitivity coefficients;

[0041] Figure 12 This is a statistical diagram of the change of exercise intensity over time under different communication scope sensitivity coefficients;

[0042] Figure 13 This is a statistical diagram of the change of exercise intensity over time under different communication scope sensitivity coefficients;

[0043] Figure 14 This is a statistical graph showing the change of exercise intensity over time under different communication scope sensitivity coefficients. DETAILED DESCRIPTION

[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0045] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains. The terms used herein in the specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "or / and" as used herein includes any and all combinations of one or more of the associated listed items.

[0046] The research based on the extended cellular machine model aims to help schools better understand and promote the physical and mental health of students by simulating the comprehensive activity behavior of boarding school students, especially their sports behavior. The model in the present invention uses an extended cellular machine (extended CA) to predict students' movement patterns, and combines the characteristics of students' daily activities, such as the different needs of learning, examinations and leisure, to analyze the spatiotemporal patterns of students' sports behavior and their key influencing factors. In view of the physical and mental health of boarding students, it is necessary to predict students' activities and then predict changes in their physical and mental states so that schools can take timely feedback actions. The present invention fixes students in a specific evolutionary space through a behavior simulation model based on an extended cellular machine, changes students' subsequent activity states through the interaction of their own activity states and the relationships between students, and the interactive relationship between students is visualized as intimacy and communication range, reducing the amount of calculation; students' activity behaviors are replaced by motion features.

[0047] Please refer to Figure 1 This embodiment provides a method for simulating student comprehensive activity behaviors based on an extended cellular machine, which simulates student comprehensive activity behaviors through a behavior simulation model based on an extended cellular machine. The method for simulating student comprehensive activity behaviors includes the following steps:

[0048] S1. Initial parameter configuration of the behavior simulation model.

[0049] Initialize the size of the student evolution space, that is, the cell space size in the model is 100*100, the total number of students is 10,000, and the space occupied by each student (each cell) is 1*1. Initialize the definition of initial parameters such as school, social orientation, and student status. These initial parameters are generally divided into environmental parameters, student sports parameters, and student status. Among them, environmental parameters include the overall probability of students joining a club, the overall probability of students winning awards, whether the school has sports infrastructure, and the time ratio of students to and from classes. Student sports parameters include the sensitivity coefficient k of sports characteristics S , sensitivity coefficient k of intimacy L and the sensitivity coefficient k of the communication scope R The student status includes the student's gender, grade, type of sports, intensity of sports, time spent on sports, whether the student has joined a club, and whether the student has won an award. The student status is defined as shown in the following table:

[0050]

[0051] Furthermore, ignoring other special external conditions, students' exercise status evolves into three stages as time progresses: 1. The first stage is the leisure study period. During this stage, class time is short, while breaks and after-school hours are long. This allows students to devote more time to exercise, and students can easily influence each other, expanding their participation in exercise. 2. The second stage is the regular study period. During this stage, class time increases, but students' free time gradually decreases, weakening their interaction with exercise. 3. The third stage is the critical exam period. During this stage, breaks and after-school hours are shortened, and academic pressure is high. Students' free time decreases dramatically, making them less inclined to exercise and less susceptible to being influenced by the activities of their surrounding students. As time progresses, these three stages cycle through the following order: regular study period -> leisure study period -> regular study period -> critical exam period.

[0052] S2. Calculate the transition probability of cells in the behavioral simulation model.

[0053] In the behavior simulation model based on the extended cellular machine, the student's related behavior changes are affected by the adjacent cells. The definition of adjacent cells is shown in the following table:

[0054]

[0055] On the other hand, all the changes in the state of the student's motion characteristics in each time step will be affected by the adjacent student states, evolutionary stages, and environmental parameters. The corresponding cell transition probability calculation formula is as follows:

[0056]

[0057] Where i represents the index of the horizontal coordinate of the student's evolution range (in the cell space). j represents the index of the vertical coordinate of the student's evolution range. z represents the index or parameter of all the student's changeable motion features. N is the adjustment parameter to ensure that p i,j,k ≤1. S ijz Indicates that the current student’s z-th motion feature is affected by the same motion feature of the rest of the students and the rest of the motion features. ij Indicates intimacy. The higher the intimacy between students, the more likely they are to change their sports characteristics. ij Indicates the student's social circle. The larger the social circle, the more people can be influenced, and the lower the influence of a single student. S ,k L ,k R, are the sensitivity coefficients of movement characteristics, intimacy, and communication scope respectively. E represents the environmental parameter. H Indicates holiday time, T C Indicates time spent in school. Different time periods have different effects on students' exercise status.

[0058] Among them, the above motion feature S ijz The expression is:

[0059]

[0060] In the formula, F is the adjustment parameter of the motion feature, and S is changed according to the value of the following formula. ijz 。St ij For the current student movement type. St xy Sp is the movement type of other students (x, y) in the current student's communication range. ij The current student exercise intensity. xy Sd is the exercise intensity of other students (x, y) within the current student’s communication range. ij is the current student exercise time frequency. xy Sjc is the movement time frequency of other students (x, y) in the current student’s communication range. ij For current students, whether to join the club. xy Whether other students (x, y) in the current student's social circle have joined the club. ij Whether the current student has won an award. xy Whether the other students (x, y) in the current student’s communication range have won the award. t ,k p ,k d ,k jc ,k r St ij ,Sp ij ,Sd ij ,Sjc ij ,Sr ij Parameter coefficients of the five motion states. The motion characteristics are composed of five motion parameters. For each student's motion characteristics analysis, it can be divided into individual motion parameters z for analysis, which will help to understand the subsequent analysis of the motion characteristics. Different motion parameters z are defined as 1, 2, 3, 4, and 5. When z = 1, it means that the motion type in the motion characteristics is selected for analysis. The formula can be expressed as:

[0061] Similarly, when z=2, S ijz =Sp ij ; When z=3, S ijz =Sdij ; When z=4, S ijz =Sjc ij ; When z=5, S ijz =Sr ij .

[0062] The intimacy L in the above formula ij The expression is:

[0063]

[0064] Where, L ij Indicates the intimacy between the target student and other students in the communication range (coordinates (x, y)). xy Indicates the closeness of other students to the target student. G ij Indicates the gender of the target student. G xy Indicates the gender of other students at the coordinate (x, y). The gender definition value can be shown as the gender parameter in the table above. k ijxy The weight of the special relationship is determined by the bond between the two students, and its value will also change, ranging from [0.5-2.0]. ij It represents the communication scope of students, and its expression is:

[0065]

[0066] Where Max is the maximum communication range set. set is the average intimacy threshold set; W represents the weight of parameters such as gender and bond between students, and W>1, compared with the intimacy L ij In terms of communication scope R ij The gender parameters are not given much weight; ij Indicates the grade of the target students; C xy Indicates the corresponding grade of other students at coordinate (x, y).

[0067] S3. Calculate the student's final movement probability P ijz .

[0068] Determine the current time step. If the current evolution stage is judged to be in the leisure learning period, then perform the exercise with probability r = α. If the current evolution stage is judged to be the regular learning period, then perform the exercise with probability r = β. If the current evolution stage is judged to be the key examination period, then perform the exercise with probability r = γ. Among them, α, β and γ are all reference probabilities, and 1>α>β>γ. At the same time, record the student's various exercise conditions and time. The final student's final exercise probability P is obtained. ijz Satisfies the following formula:

[0069] P ijz =KT u rpi,j,z

[0070] Where K represents the adjustment parameter; T u Indicates the ratio of available motion time to unavailable motion time in the time step. ijz The larger it is, the more likely the student is to exercise.

[0071] S4. Parameter update.

[0072] Students will adjust their motion characteristics over the course of a semester and tend to imitate or follow students with whom they have a higher intimacy. Therefore, we introduce an update quantity: we assume that students will modify their intimacy and change their motion characteristics at each time step. In this step, we compare the current time step with the previous time step to determine whether the student's current motion state has changed, and calculate the student's current intimacy. If the student's current motion state has not changed, the sensitivity coefficient k of the motion characteristic is s If the student's current motion state changes, the sensitivity coefficient k of the motion feature will s If the current intimacy is greater than or equal to the set threshold (generally set to 0.5), the sensitivity coefficient k of the intimacy is L Increase Δσ, and the intimacy is less than the threshold, then the sensitivity coefficient k of intimacy L Reduce Δσ.

[0073] S5, the sensitivity coefficient k of the changed motion feature s and the sensitivity coefficient k of intimacy L Substitute into the next time step and repeat S2 to S5 until the end of the simulation, completing the simulation of students' activity behaviors within the set period, and providing a basis for schools to formulate reasonable sports plans and resource allocation.

[0074] In summary, the student comprehensive activity behavior simulation method in this embodiment, during the parameter configuration phase, not only sets the basic attributes of the students but also sets exercise-related parameters, including exercise type, intensity, duration, and whether or not to join a club. During the parameter adjustment and optimization phase, the model's effectiveness is ensured by adjusting and optimizing the parameters. The simulation method then enters the phase of determining movement changes and movement characteristics. If movement changes occur, the degree of influence between students is calculated, and movement behavior is adjusted accordingly. The model collects statistics on students' behavior at different time periods, including a comprehensive assessment of exercise time and intensity. Based on this, the effects of the parameters are evaluated to verify the model's accuracy and guide future adjustments. Throughout this process, intimacy is a key parameter that influences student interaction: the higher the intimacy, the greater the likelihood that students will change their movement characteristics. Furthermore, social reach is an important factor: a larger social reach influences more students, but the proportion of influence on a single student decreases. By continuously adjusting and optimizing these parameters, accurate simulation and analysis of student movement behavior is ultimately achieved, helping schools better understand and promote student well-being.

[0075] In addition, during the simulation process, all states are statistically analyzed, and the parameters of the simulated student comprehensive activity behavior are evaluated and verified. First, the initial school, social environment, and student sports parameters are set: the overall probability of students joining the club is set to 0.2; the overall probability of students winning is set to 0.05; the school has a student sports foundation set to true; the ratio of students' class time to their get out of class time is set to 8:2; the sensitivity coefficient k of the sports characteristics is set to 0. S 3, the sensitivity coefficient k of intimacy L The sensitivity coefficient k of the communication range is 1.5. R =1; finally, observe and count the average movement status of students. Figure 2 、 Figure 3 、 Figure 4 、 Figure 5 、 Figure 6 、 Figure 7 、 Figure 8 and Figure 9 .Depend on Figures 2 to 9 It can be seen that students will gradually follow each other over time. Under the pressure of regular study period, they gradually reduce their exercise time and intensity ( Figures 2 to 7In the figure, power is the intensity of exercise, and duration is the duration of exercise. Red represents intensity 1 (level 1) or a duration <30, green represents intensity 2 (level 2) or a duration 30-60, and blue represents intensity 3 (level 3) or a duration >60). This is because students lack enthusiasm for exercise after studying hard. When T is 20-40, which is set as the vacation period or leisure study period, students have almost no academic pressure and have plenty of time to relax. Students are more inclined to exercise, and are more likely to choose higher intensity and duration of exercise. After T>40, the pressure of study is relieved, and students will reduce the intensity and duration of exercise, but they will not stop exercising completely. When T is between 70-90, which is set as the exam week or the key exam period, students' exercise time is drastically compressed, and their exercise intensity and duration are directly reduced to the lowest level.

[0076] This suggests that during regular study periods, when students face relatively little academic pressure, schools can appropriately reduce their involvement in student activities and allow students to arrange their own exercise time. However, during exam weeks and key test periods, schools should pay special attention to relieving students' academic pressure and adopt appropriate measures to encourage them to increase their enthusiasm for exercise. This can include making physical education courses more engaging, hosting enjoyable sports activities, or providing incentives to encourage students to participate in physical exercise, thereby preventing prolonged periods of physical inactivity from negatively impacting their physical and mental health.

[0077] Then we evaluate and analyze the effect of each sensitivity coefficient. s The value of corresponds to the change of the average movement characteristics of the observed students. The sensitivity coefficient k of the movement characteristics s As the horizontal axis, the motion characteristics as the vertical axis, the results are as follows Figure 10 Take swimming as an example, and combine Figure 10 As shown, without considering the exam week and holiday week, the sensitivity coefficient k of the motion feature is s When k is low, the student's movement characteristics are relatively stable and will not change significantly over time, indicating that the student basically maintains his or her own exercise habits and is less affected by the exercise habits of others. Even if influenced by others, he or she will not easily change his or her exercise method. s = 8, which is converted into a code that shows a double tendency to follow others. Students will be more inclined to follow others at the beginning. Figure 10 It can be seen that most students tend to follow other sports (such as basketball and football) in the beginning, resulting in a small number of swimmers. As time goes by, the number of students tends to be stable, and the students' exercise habits have been formed and tend to be stable. sWhen k is low, students usually maintain their own exercise habits and are less likely to be influenced by the exercise habits of others. Therefore, schools can stimulate students' interest in sports by offering a variety of sports courses and facilities, and encourage students to try new sports to enrich their sports experience. s When the score is higher, students are more easily influenced by their peers. Schools can take advantage of this and organize team sports or competitions to enhance interaction among students and encourage more students to participate in sports.

[0078] Sensitivity coefficient k to intimacy L Analysis of the effect of changing the sensitivity coefficient k of intimacy L The value of corresponds to the average movement characteristic change of the observed students. The sensitivity coefficient k of intimacy L As the horizontal axis, the motion characteristics as the vertical axis, the results are as follows Figure 11 As shown. Figure 11 It can be seen that the sensitivity coefficient k L and sensitivity coefficient k s The change curve is similar to that of , and high intimacy will make students more inclined to follow the movement. Once the intimacy decreases, the influence of intimacy on the overall movement characteristics of students will drop sharply. In general, the average movement performance of students will change steadily and will not be affected by intimacy. The sensitivity coefficient k for intimacy L The analysis of the effects indicates that high intimacy leads students to be more inclined to follow others' exercise behaviors. Therefore, schools should create opportunities for students to build closer relationships, such as organizing team-building activities or group sports to foster friendships and enhance the collective atmosphere. Meanwhile, when intimacy is low, changes in student exercise behavior are relatively stable and unaffected by external influences. In this case, schools can consider strengthening individual exercise plans to help students develop independent exercise habits.

[0079] Sensitivity coefficient k to communication scope R Analysis of the role of: changing the sensitivity coefficient k of the communication scope R The value of corresponds to the change of the average movement characteristics of the observed students. The sensitivity coefficient k of the communication range R As the horizontal axis, the motion characteristics as the vertical axis, the results are as follows Figure 12 、 Figure 13 and Figure 14 As shown. Figure 8 and Figure 9 Compared with the reference, it can be concluded that when the sensitivity coefficient k is reduced R When the sensitivity coefficient k is increased, the influence of the communication range on the changes of students' movement characteristics will be reduced, which will weaken the students' tendency to follow, causing the students' movement state to tend to be random, and the overall student average state to tend to be uniformly distributed and stable. R, which leads to a greater impact of the communication scope on the changes in students' movement status. Students have a wider range of options to follow, and their subjectivity is poor. They will continue to follow others' movement status, resulting in a more fixed change in the movement status of a single student. The sensitivity coefficient k for the communication scope is R Analysis shows that when the social circle is small, students' exercise behavior is more random. However, when the social circle is large, students tend to imitate others' exercise behaviors. Therefore, schools should actively organize group exercise activities on campus to expand students' social circle and improve their social skills. At the same time, organizing various sports events or interest groups can broaden students' horizons and promote their physical and mental health.

[0080] In general, during regular study periods, schools can appropriately reduce their intervention in student exercise; during exam periods, measures should be taken to alleviate students' learning pressure and encourage them to maintain moderate exercise. At the same time, schools should encourage a variety of sports programs and promote interaction among students to cultivate good exercise habits. When formulating sports plans and allocating resources, schools should fully consider the impact of these factors on students' exercise behavior, comprehensively consider the needs and behavioral characteristics of students at different stages, flexibly adjust strategies, focus on organizing collective activities while also paying attention to individual differences, rationally arrange sports courses, create a positive and healthy campus sports atmosphere, stimulate students' enthusiasm for sports through various channels, and promote their physical and mental health and all-round development.

[0081] In another embodiment, the present invention further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the student comprehensive activity behavior simulation method disclosed in the above embodiment is implemented. The computer-readable storage medium includes a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., an SD or DX memory), a magnetic memory, a disk, an optical disk, etc., for storing and installing application software and an executable computer program that implement the student comprehensive activity behavior simulation method based on the extended cellular machine.

[0082] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0083] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the patent for this invention shall be determined by the appended claims.

Claims

1. A method for simulating student comprehensive activity behaviors based on an extended cellular machine, characterized in that: The method simulates students' comprehensive activity behaviors through a behavior simulation model based on an extended cellular machine; the method comprises the following steps: S1. Initial parameter configuration of the behavior simulation model; S2. Calculate the cell transfer probability p i,j,z , and its calculation formula is: Where i represents the index of the student's horizontal coordinate in the cellular space; j represents the index of the student's vertical coordinate in the cellular space; z represents the index of all the student's changeable motion features; N is the adjustment parameter; S ijz Indicates the zth motion feature of the current student; L ij Indicates the closeness between students; R ij Indicates the student's communication scope; k S ,k L ,k R are the sensitivity coefficients of movement characteristics, intimacy, and social scope respectively; E represents the environmental parameter; T H Indicates holiday time, T C Indicates time spent in school; S3. Calculate the student's final movement probability P ijz , and its calculation formula is: P ijz =KT u rp i,j,z Where K represents the adjustment parameter; T u represents the ratio of available exercise time to unavailable exercise time in the time step; r represents the evolution stage of the current time step. If the evolution stage is judged to be the leisure learning period, exercise is performed with probability r = α; if the evolution stage is judged to be the regular learning period, exercise is performed with probability r = β; if the evolution stage is judged to be the key examination period, exercise is performed with probability r = γ; where α, β, and γ are all reference probabilities, and 1>α>β>γ; S4. Compare the current time step with the previous time step to determine whether the student's current motion state has changed, and calculate the student's current intimacy; if the student's current motion state has not changed, the sensitivity coefficient k of the motion feature s remains unchanged; if the student's current motion state changes, the sensitivity coefficient k of the motion feature s Reduce Δδ; if the current intimacy is greater than or equal to the set threshold, the sensitivity coefficient k of the intimacy L Increase Δσ, and the intimacy is less than the threshold, then the sensitivity coefficient k of intimacy L Reduce Δσ; S5, the sensitivity coefficient k of the changed motion feature s and the sensitivity coefficient k of intimacy L Substitute the next time step and repeat S2 to S5 until the simulation ends.

2. The method for simulating student comprehensive activity behaviors based on an extended cellular machine according to claim 1, characterized in that: The cell space of the behavior simulation model is 100*100, and the neighborhood type is Moore type; each cell occupies a space of 1*1.

3. The method for simulating student comprehensive activity behaviors based on an extended cellular machine according to claim 1, characterized in that: The initial parameters include environmental parameters, student sports parameters and student status; the environmental parameters include the overall probability of students joining the club, the overall probability of students winning awards, whether the school has sports infrastructure and the time ratio of students to and from classes; the student sports parameters include the sensitivity coefficient k of the sports characteristics S , sensitivity coefficient k of intimacy L and the sensitivity coefficient k of the communication scope R The student status includes the student's gender, the student's sports type, the student's sports intensity, the student's sports time, whether the student joins a club, and whether the student has won an award.

4. The method for simulating student comprehensive activity behaviors based on an extended cellular machine according to claim 1, characterized in that: The motion feature S ijz The expression is: Where F is the adjustment parameter of motion characteristics; St ij is the current student sports type; St xy The sports types of other students in the current student's social circle; Sp ij is the current student exercise intensity; Sp xy Sd is the exercise intensity of other students in the current student's social circle; ij is the current student exercise time frequency; Sd xy The movement time frequency of other students in the current student's communication range; Sjc ij Whether the current student joins the club; Sjc xy Whether other students in the current student's social circle join the club; ij Whether the current student has won an award; Sr xy Whether other students in the current student's social circle have won awards; k t ,k p ,k d ,k jc ,k r St ij ,Sp ij ,Sd ij ,Sjc ij ,Sr ij Parameter coefficients of the five motion states.

5. The method for simulating student comprehensive activity behavior based on an extended cellular machine according to claim 1, characterized in that: The intimacy L ij The expression is: Where, L ij Indicates the closeness between the target student and other students in the communication range; L xy Indicates the closeness of other students to the target student; G ij Indicates the gender of the target student; G xy Indicates the gender of other students at the coordinate (x, y); k ijxy Represents the weight of the special relationship; R ij Indicates the student's communication scope.

6. The method for simulating student comprehensive activity behavior based on an extended cellular machine according to claim 5, characterized in that: The communication range R ij The expression is: Where Max is the maximum communication range set; L set is the average intimacy threshold set; W represents the weight of gender and bond between students, and W>1; C ij Indicates the grade of the target students; C xy Indicates the corresponding grade of other students at coordinate (x, y).

7. The method for simulating student comprehensive activity behaviors based on an extended cellular machine according to claim 1, characterized in that: In S3, the evolution stage is divided into three stages: leisure learning period, regular learning period and key examination period; among them, the leisure learning period is characterized by less class time and more rest time and after-school time; the regular learning period is characterized by more class time and gradually less free time for students; the key examination period is characterized by shorter rest time and after-school time, and a sharp decrease in students' free time.

8. The method for simulating student comprehensive activity behaviors based on an extended cellular machine according to claim 6, characterized in that: The three evolutionary stages are cyclically performed in a changing order, and the changing order is regular learning period - leisure learning period - regular learning period - key examination period.

9. The method for simulating student comprehensive activity behavior based on an extended cellular machine according to claim 1, characterized in that: After simulating the students' comprehensive activity behaviors, parameter evaluation is performed; the parameter evaluation is used to explore key factors that affect the learning activity behaviors.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for simulating student comprehensive activity behavior based on an extended cellular machine as described in any one of claims 1 to 9 is implemented.

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