Physical education course data processing method and device, and electronic equipment
By establishing an environmental inversion model and a decision-making model that combines course intensity weighting in plateau regions, the timing and intensity of courses can be dynamically adjusted, thus solving the problem of environmental adaptability in plateau physical education curriculum arrangements and improving the safety and scientific nature of plateau physical education teaching.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- JINING UNIV
- Filing Date
- 2026-04-16
- Publication Date
- 2026-07-14
AI Technical Summary
The physical education curriculum in high-altitude areas neglects the amplifying effect of topographic radiation on local temperature inversion, resulting in biased selection of class times. It fails to meet the safety requirements of exercise in the low-oxygen environment of high altitude, lacks spatiotemporal modeling of temperature inversion and a curriculum-environment coupling decision-making mechanism, and poses health risks.
By collecting environmental data and course information, an environmental inversion model is established. Combined with course intensity weights, a course duration decision model is generated to dynamically adjust course time periods and intensity. Using a terrain radiation model and radiation fluctuation update mechanism, an adaptive course ranking table is generated.
It significantly reduces the health risks of high-altitude hypoxia and ultraviolet radiation, ensures that the course duration and time period are precisely matched with environmental conditions, improves the safety and scientific nature of high-altitude physical education, and is suitable for high-altitude physical education schools with hilly terrain.
Smart Images
Figure CN122390924A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of intelligent physical education teaching technology, and in particular to a method, device and electronic equipment for processing physical education course data. Background Technology
[0002] Current physical education curricula in high-altitude areas generally rely on static environmental data and experience-based schedules, making it difficult to address complex meteorological risks such as temperature inversions and radiation fluctuations. Traditional methods have significant drawbacks: First, they ignore the amplifying effect of topographic radiation on local temperature inversions, leading to biased course timing—for example, scheduling endurance training during the top of an inversion layer where air is blocked, exacerbating the risk of decreased blood oxygen levels in students; second, the intensity of the curriculum is disconnected from physiological load, failing to establish a dynamic correlation between the aerobic / anaerobic ratio index and environmental weights, thus failing to meet the safety requirements of exercise in the low-oxygen environment of high altitudes.
[0003] While existing technologies attempt to incorporate basic meteorological monitoring, they lack spatiotemporal modeling of temperature inversions and a curriculum-environment coupled decision-making mechanism. Particularly in sloping terrain, the lack of dynamic model updates means that curriculum schedules cannot avoid health risks caused by sudden radiation changes or thickening inversion layers. This extensive management approach hinders the safety and scientific rigor of physical education in high-altitude areas. Summary of the Invention
[0004] The purpose of this invention is to provide a method, apparatus, and electronic device for processing physical education course data, so as to solve at least one of the problems existing in the prior art.
[0005] To achieve the above objectives, according to one aspect of this application, the present invention provides a method for processing physical education course data, comprising: Collect environmental data and course information for the target area; The intensity of each course is judged based on the course information, and the course intensity weight set of each physical education course is set based on the judgment results of the intensity of each course. An environmental inversion model is established based on environmental data of the target area, and then the inversion period of the target area is determined by the environmental inversion model. The radiation fluctuation state of the target area is assessed, and the environmental inversion model is updated based on the assessment results. A course duration decision model is established by combining the judgment results of the temperature inversion period in the target area with the course intensity weight set of each physical education course, and then the output results of the course duration decision model are used to generate a ranking table of each physical education course.
[0006] Optionally, the expression for the intensity index of a physical education course is as follows: A(i) = a1 × α(i) + a2 × β(i); μ(i) = α(i) / β(i); In the formula, α(i) is the aerobic ratio index of the i-th physical education course, β(i) represents the anaerobic ratio index of the i-th physical education course, A(i) represents the intensity index of the i-th physical education course, μ(i) represents the intensity index of the i-th physical education course, and a1 and a2 are the aerobic intensity weight and anaerobic intensity weight, respectively.
[0007] Optionally, a gradient intensity threshold and a course category proportion constant K are set to numerically determine the intensity index of physical education courses in order to classify each physical education course into different types. The process of categorizing the data from each physical education course is as follows: When μ(i) is less than K, the physical education course is classified as an endurance training course, and the environmental weight of the physical education course is set to exp{|μ(i)-K|}; otherwise, the physical education course is classified as a strength training course, and the environmental weight of the physical education course is set to 1; where K represents the course category ratio constant. When A(i) belongs to the Nth intensity interval, the course intensity weight of the physical education course is set as the product of exp[-1 / N] and the environmental weight of the physical education course.
[0008] Optionally, a topographic map of the target area is obtained, and the surface temperature in the topographic map is also obtained. Based on the topographic map and the surface temperature, a topographic radiation temperature space surface is constructed. Mark the coordinates of each location within the target area on the topographic map of the target area, and assign temperature values to each location coordinate using the surface temperature on the topographic map of the target area. Construct an initial topographic radiation temperature space surface based on the assignment results.
[0009] Optionally, the temperature flow vector at each position coordinate is calculated based on the marking results, and the temperature flow vector at the j-th position coordinate is denoted as b(j). b(j) is defined as the sum of the vectors from the adjacent position coordinates to the j-th position coordinate, where j is the numerical subscript of the position coordinate. Then, the temperature inversion index γ(j) at each position coordinate is calculated by combining the temperature flow vector at each position coordinate with the temperature at each position coordinate. In the formula, bθ(j) represents the angle of the temperature flow vector at the j-th position relative to the ground plane, and B represents the standard value of change. The product of the temperature at the j-th location coordinate, the inversion temperature change index γ(j) at the j-th location coordinate, and the time interval G is used as the predicted topographic radiation temperature spatial surface for each time period.
[0010] Optionally, the inversion layer thickness and temperature for each time period are obtained based on the predicted topographic radiation temperature spatial surface of the target area for each time period. If the inversion layer thickness is less than the inversion layer thickness threshold Q in the k-th time period, the time period is defined as an inversion time period. If the inversion layer thickness is greater than or equal to the inversion layer thickness threshold Q and the inversion layer temperature is greater than T in the k-th time period, the time period is defined as the top inversion time period. If the inversion layer thickness is greater than or equal to the inversion layer thickness threshold Q and the inversion layer temperature is less than or equal to T in the k-th time period, the time period is defined as the bottom inversion time period. T is the time period division temperature.
[0011] Optionally, the surface thermal radiation intensity at each location coordinate can be collected based on the topographic map of the target area; Calculate the radiation intensity weight W(j) for each location coordinate, and set W(j) = {HB(j) - min{HB(j)}} / {cos[bθ(j)] × L}; where HB(j) represents the altitude of the j-th location coordinate, and L is the longest slope length of the target area; The product of the radiation intensity weight of each location coordinate and the surface thermal radiation intensity of the corresponding location coordinate is used as the radiation intensity index of each location coordinate. A radiation intensity threshold is set. When the radiation intensity index of the j-th location coordinate is greater than or equal to the radiation intensity threshold, the inversion temperature change index of the j-th location coordinate is updated to γr(j).
[0012] Optionally, when the i-th physical education course is an endurance training course, the inversion period is selected as the course period of the i-th physical education course, and the course duration of the physical education course is set to KT1(i). The value of KT1(i) is set to the product of the ratio of the baseline duration to the course intensity weight of the i-th physical education course and the temperature offset ratio of the target area in the k-th time period relative to T. When the i-th physical education course is a strength training course, the top time period of the temperature inversion is selected as the course time period of the i-th physical education course, and the course duration of the physical education course is set to KT3(i). The value of KT3(i) is set to be the ratio of η times the base duration to the course intensity weight of the i-th physical education course. A ranking table of physical education courses is generated based on the course duration and time slot of each course.
[0013] According to another aspect of this application, a physical education course data processing device is provided, comprising: The data acquisition unit is used to collect sports data of the target users, as well as environmental data and course information of the target area; The intensity weight setting unit is used to judge the intensity of each course based on the course information, and to set the course intensity weight set of each physical education course based on the judgment results of the intensity of each course. The temperature inversion analysis unit is used to establish an environmental temperature inversion model based on the environmental data of the target area, and then use the environmental temperature inversion model to determine the temperature inversion period of the target area. The inversion update unit is used to determine the radiation fluctuation state of the target area and update the environmental inversion model based on the determination result. The decision generation unit is used to establish a course duration decision model by combining the judgment results of the inversion period in the target area with the course intensity weight set of each physical education course, and then generate a ranking table of each physical education course based on the output of the course duration decision model.
[0014] According to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, wherein the computer program is used to control the electronic device on which the computer-readable storage medium is located to execute the aforementioned physical education course data processing method during runtime. Compared with existing technologies, the beneficial effects of this invention are as follows: This invention solves the environmental adaptability problem in the arrangement of physical education courses in plateau areas through multi-dimensional data fusion and dynamic modeling. Its core value lies in: significantly reducing the health risks of hypoxia and ultraviolet radiation at high altitudes by dividing the time according to temperature inversion periods and combining user blood oxygen data; ensuring that course duration and time periods are accurately matched with environmental conditions and exercise types through dynamic coupling of course intensity weights and environmental weights; realizing the adaptive generation of course ordering tables based on terrain radiation models and radiation fluctuation update mechanisms, improving the scientific nature and safety of physical education in plateau areas; and ultimately maximizing training effects while ensuring user health, especially suitable for plateau physical education school scenarios with hilly terrain. Attached Figure Description
[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0016] Figure 1 This is a flowchart illustrating the data processing method for physical education courses in this embodiment.
[0017] Figure 2 This is a flowchart illustrating the method for setting the course intensity weight set in this embodiment.
[0018] Figure 3 This is a flowchart illustrating the method for determining the inversion period in this embodiment.
[0019] Figure 4 This is a schematic diagram of the structure of the electronic device provided in this embodiment.
[0020] Figure 5 This is a schematic diagram of the physical education course data processing device provided in this embodiment. Detailed Implementation
[0021] To more clearly illustrate the present invention, the following description, in conjunction with preferred embodiments and accompanying drawings, further explains the invention. Similar components in the drawings are indicated by the same reference numerals. Those skilled in the art should understand that the specific description below is illustrative rather than restrictive and should not be construed as limiting the scope of protection of the present invention.
[0022] It should be noted that although the terms first, second, third, etc., may be used in the embodiments of this application for description, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of this application, first can also be referred to as second, and similarly, second can also be referred to as first.
[0023] The acquisition, storage, use, and processing of data in this application all comply with the relevant provisions of national laws and regulations.
[0024] Specifically, the physical education curriculum data processing method described in this application is applied to physical education curriculum data processing conducted in physical education schools in plateau areas; the physical education curriculum data processing in plateau areas described in this application involves comprehensive processing of blood oxygen, ultraviolet radiation, temperature inversion layer and curriculum intensity in plateau physical education courses, so as to obtain a reasonable physical education curriculum schedule based on physical education curriculum data; furthermore, the physical education school described in this application is a physical education school located on a plateau hillside.
[0025] To apply the above-mentioned application scenarios, this application provides a method for processing physical education course data, the flowchart of which can be found in the document. Figure 1 As shown, it includes: Step S101: Collect environmental data and course information of the target area; the environmental data of the target area includes: the surface temperature of the target area; the course information includes: the baseline duration and the historical exercise duration of the physical education course.
[0026] Specifically, the target users described in this application can be students, trainers, or other personnel involved in physical education training courses; at the same time, the collection of the target users' sports data in this application can be carried out in real time through wearable devices; the target area is the area where the target users conduct sports activities.
[0027] Please continue reading. Figure 1 As shown, the physical education course data processing method further includes: Step S102: Determine the intensity of each course based on the course information, and set the course intensity weight set for each physical education course based on the determination results of the intensity of each course.
[0028] To implement the method in step S102 of this application, this application also provides, as follows: Figure 2 The flowchart illustrating the method for setting the course intensity weight set shows the following: Step S201: Construct the intensity index of each physical education course based on the course information.
[0029] Specifically, in step S201, the process of classifying the intensity levels of each physical education course is as follows: The expression for the intensity index of physical education courses is as follows: α(i) = YT(i) / LT(i); β(i) = WT(i) / LT(i); A(i) = a1 × α(i) + a2 × β(i); μ(i) = α(i) / β(i); In the formula, α(i) is the aerobic ratio index of the i-th physical education course, β(i) represents the anaerobic ratio index of the i-th physical education course, A(i) represents the intensity index of the i-th physical education course, μ(i) represents the intensity index of the i-th physical education course, a1 and a2 are the aerobic intensity weight and anaerobic intensity weight, respectively, WT(i) is the anaerobic exercise duration of the i-th physical education course, YT(i) is the aerobic exercise duration of the i-th physical education course, and LT(i) is the historical exercise duration of the i-th physical education course.
[0030] For example, in this application, the blood oxygen consumption rate can be used as the construction weight of the aerobic ratio index, and the maximum lactate concentration can be used as the construction weight of the anaerobic ratio index.
[0031] Specifically, by quantitatively defining the aerobic proportion index α(i), the anaerobic proportion index β(i), and the comprehensive intensity index A(i), the physiological load characteristics of physical education courses are transformed into a calculable mathematical model. This step provides an objective standard for course classification, avoiding the subjective bias of traditional experience-based judgments. Especially in high-altitude, low-oxygen environments, accurate intensity indices can directly correlate with blood oxygen consumption efficiency, laying a data foundation for subsequent environmental adaptation decisions.
[0032] Please continue reading. Figure 2 As shown, the method for setting the course intensity weight set further includes: Step S202: Classify each physical education course according to its intensity index, and set a course intensity weight set for each physical education course based on the classification results. The gradient intensity threshold in this application includes multiple intensity thresholds, and each intensity threshold forms an intensity interval. Except for the last intensity interval, each intensity interval is a left-closed and right-open interval.
[0033] Specifically, in step S202, the process of setting course intensity weights is as follows: The intensity index of physical education courses is numerically determined by setting a gradient intensity threshold and a course category proportion constant K, so as to classify each physical education course into different types. The process of categorizing the data from each physical education course is as follows: When μ(i) is less than K, the physical education course is classified as an endurance training course, and the environmental weight of the physical education course is set to exp{|μ(i)-K|}; otherwise, the physical education course is classified as a strength training course, and the environmental weight of the physical education course is set to 1; where K represents the course category ratio constant. When A(i) belongs to the Nth intensity interval, the course intensity weight of the physical education course is set as the product of exp[-1 / N] and the environmental weight of the physical education course.
[0034] Specifically, this application does not impose specific limitations on the value of the course category ratio constant. Those skilled in the art can set it freely, as long as the value requirement of the course category ratio constant is met. In this application, the optimal value of the course category ratio constant can be set to 0.85.
[0035] Specifically, based on the course category ratio constant K and gradient intensity threshold, endurance / strength course types are dynamically divided by ratio. An innovative environmental weight is introduced, making the course intensity weight set both athletic and environmentally sensitive. This design significantly improves the adaptability of high-altitude course arrangements and strengthens the need to avoid temperature inversion environments.
[0036] Please continue reading. Figure 1 As shown, the physical education course data processing method further includes: Step S103: Establish an environmental inversion model based on the environmental data of the target area, and then use the environmental inversion model to determine the inversion period of the target area.
[0037] To implement the method in step S103 of this application, this application also provides, as follows: Figure 3 The flowchart illustrating the method for determining the inversion period shows the following: Step S301: Establish an environmental inversion model based on the environmental data of the target area.
[0038] Specifically, in step S301, the process of establishing the environmental inversion model is as follows: Obtain a topographic map of the target area and its surface temperature. Based on the topographic map and surface temperature, construct a topographic radiation temperature space surface. Mark the coordinates of each location within the target area on the topographic map of the target area, and assign temperature values to each location coordinate using the surface temperature in the topographic map of the target area. Construct an initial topographic radiation temperature space surface based on the assignment results. The temperature flow vector at each position coordinate is calculated based on the marking results, and the temperature flow vector at the j-th position coordinate is denoted as b(j). b(j) is defined as the sum of the vectors from the adjacent position coordinates to the j-th position coordinate, where j is the numerical subscript of the position coordinate. Then, the temperature inversion index γ(j) at each position coordinate is calculated by combining the temperature flow vector at each position coordinate with the temperature at each position coordinate. In the formula, bθ(j) represents the angle of the temperature flow vector at the j-th position relative to the ground plane, and B represents the standard value of change. The product of the temperature at the j-th location coordinate, the inversion temperature change index γ(j) at the j-th location coordinate, and the time interval G is used as the predicted topographic radiation temperature spatial surface for each time period.
[0039] It is understood that the phrase "using the product of the temperature at the j-th location coordinate with the inversion temperature change index γ(j) at the j-th location coordinate and the time interval G as the predicted topographic radiation temperature spatial surface for each time period" in this application can be more specifically interpreted as follows: using the product of the temperature at the j-th location coordinate with the inversion temperature change index γ(j) at the j-th location coordinate as the value of the j-th location node in the predicted topographic radiation temperature spatial surface for the first time period; using the product of the temperature at the j-th location coordinate with the inversion temperature change index γ(j) at the j-th location coordinate and G as the value of the j-th location node in the predicted topographic radiation temperature spatial surface for the second time period; using the product of the temperature at the j-th location coordinate with the inversion temperature change index γ(j) at the j-th location coordinate and 2×G as the value of the j-th location node in the predicted topographic radiation temperature spatial surface for the third time period, and so on.
[0040] For example, the time interval G mentioned in this application is a standard time period for inversion analysis, and its dimension is hours. In this application, 0.67 is used as the value of the time interval G. Those skilled in the art can also set it themselves, as long as the time interval G is less than 6. At the same time, the change standard value mentioned in this application is the benchmark value of the inversion change index. This application does not specifically limit its value. Those skilled in the art can set it freely. The optimal value of the change standard value provided in this application is 0.707.
[0041] Specifically, the process of establishing the environmental inversion model of the target area in this application is only carried out within the time interval between 6:00 and 18:00. That is, this application does not conduct a specific analysis of the inversion phenomenon caused by the alternation of day and night. At the same time, the specific process of "marking the coordinates of each location within the target area on the topographic map of the target area" in this application can take the center position of each 1 square meter on the topographic map of the target area as a location coordinate, and the location coordinate is a coordinate in a three-dimensional rectangular coordinate system.
[0042] Specifically, by utilizing the topographic radiation temperature spatial surface and temperature flow vector, an inversion change index at the location coordinate level is established. By predicting the topographic radiation temperature spatial surface, a refined simulation of the spatiotemporal evolution of inversions is achieved. This model overcomes the coarse-grained limitations of traditional meteorological data, accurately capturing the local inversion characteristics of hillside terrain, and providing centimeter-level environmental insights for selecting time periods for plateau courses.
[0043] Please continue reading. Figure 3 As shown, the method for determining the inversion period also includes: Step S302: Determine the inversion thickness of the target area based on the topographic radiation temperature spatial surface, and determine the inversion period by setting an inversion thickness threshold.
[0044] Specifically, in step S302, the process for determining the inversion period is as follows: Based on the predicted topographic radiation temperature spatial surface of the target area for each time period, the inversion layer thickness and temperature for each time period are obtained. When the inversion layer thickness is less than the inversion layer thickness threshold Q in the k-th time period, the time period is defined as an inversion time period. When the inversion layer thickness is greater than or equal to the inversion layer thickness threshold Q and the inversion layer temperature is greater than T in the k-th time period, the time period is defined as the top inversion time period. When the inversion layer thickness is greater than or equal to the inversion layer thickness threshold Q and the inversion layer temperature is less than or equal to T in the k-th time period, the time period is defined as the bottom inversion time period. T is the temperature for dividing the time period.
[0045] For example, the value of the inversion layer thickness threshold Q in this application can be set by those skilled in the art, as long as the value requirement of the inversion layer thickness threshold Q is met. In this application, since the target area is about 50 meters higher than the valley area, the inversion layer threshold can be set to 50 meters. At the same time, the value of the time period division temperature T can be 110% of the ground temperature of the target area.
[0046] It is understood that the inversion period mentioned in this application means that the target area is in the inversion layer, during which the temperature is lower than the normal temperature, but is in the stage of temperature rise; the top inversion period means that the target area is in the top layer of the inversion layer, during which air circulation is blocked, and it is not suitable for aerobic sports training; the lower inversion period means that the target area is outside the inversion layer and the temperature is in the stage of temperature drop.
[0047] Specifically, by combining the inversion layer thickness threshold and temperature threshold, the time period is divided. This classification is directly related to sports safety—the top layer period, when air circulation is blocked, can easily cause hypoxia, while the temperature rise during the inversion period can reduce the risk of cold injury. The decision-making logic closely matches the physiological protection needs of high altitude.
[0048] Please continue reading. Figure 1 As shown, the physical education curriculum data processing method further includes: Step S104: Determine the radiation fluctuation state of the target area and update the environmental inversion model based on the determination result.
[0049] Specifically, in step S104, the update process for the environmental inversion model is as follows: The surface thermal radiation intensity at each location is collected based on the topographic map of the target area; Calculate the radiation intensity weight W(j) for each location coordinate, and set W(j) = {HB(j) - min{HB(j)}} / {cos[bθ(j)] × L}; where HB(j) represents the altitude of the j-th location coordinate, and L is the longest slope length of the target area; The product of the radiation intensity weight of each location coordinate and the surface thermal radiation intensity of the corresponding location coordinate is used as the radiation intensity index of each location coordinate. A radiation intensity threshold is set. When the radiation intensity index of the j-th location coordinate is greater than or equal to the radiation intensity threshold, the inversion temperature change index of the j-th location coordinate is updated to γr(j), and γr(j) is set to γr(j) / HB(j).
[0050] Specifically, this application does not impose specific limitations on the value of the radiation intensity threshold. Those skilled in the art can set it freely, as long as the value requirement of the radiation intensity threshold is met. In this application, the optimal value of the radiation intensity threshold can be set to 0.6.
[0051] Specifically, the amplification effect of terrain on thermal radiation is quantified by using radiation intensity weights. When the radiation intensity index exceeds a threshold, the inversion change index is dynamically updated to reduce inversion prediction errors in high-altitude areas. This step significantly improves the model's reliability in strong sunlight scenarios (such as midday at high altitudes) and avoids misjudgments of course safety due to sudden changes in radiation.
[0052] Please continue reading. Figure 1 As shown, the physical education course data processing method further includes: Step S105: Based on the judgment results of the temperature inversion period in the target area and the course intensity weight set of each physical education course, a course duration decision model is established, and then the output results of the course duration decision model are used to generate a ranking table of each physical education course.
[0053] Specifically, in step S105, the process of establishing the course duration decision model is as follows: When the i-th physical education course is an endurance training course, the inversion period is selected as the course period of the i-th physical education course, and the course duration of the physical education course is set to KT1(i). The value of KT1(i) is the product of the ratio of the baseline duration to the course intensity weight of the i-th physical education course and the temperature offset ratio of the target area of the k-th time period relative to T. When the i-th physical education course is a strength training course, the top time period of the temperature inversion is selected as the course time period of the i-th physical education course, and the course duration of the physical education course is set to KT3(i). The value of KT3(i) is set to be the ratio of η times the base duration to the course intensity weight of the i-th physical education course. A ranking table of physical education courses is generated based on the course duration and time slot of each course.
[0054] Specifically, the final generated course sequence achieves the dual objectives of "minimizing environmental risks" and "maximizing training efficiency," especially ensuring the safety of endurance training in low-oxygen environments.
[0055] For example, the baseline duration mentioned in this application is 40 minutes. Those skilled in the art can set it freely, as long as the baseline duration requirement is met. In this application, the baseline duration refers to the duration of the initial physical education course.
[0056] Please see Figure 4 As shown, it is a schematic diagram of the structure of the physical education course data processing device provided in this application, including: The data acquisition unit is used to collect sports data of the target users, as well as environmental data and course information of the target area; The intensity weight setting unit is used to judge the intensity of each course based on the course information, and to set the course intensity weight set of each physical education course based on the judgment results of the intensity of each course. The temperature inversion analysis unit is used to establish an environmental temperature inversion model based on the environmental data of the target area, and then use the environmental temperature inversion model to determine the temperature inversion period of the target area. The inversion update unit is used to determine the radiation fluctuation state of the target area and update the environmental inversion model based on the determination result. The decision generation unit is used to establish a course duration decision model by combining the judgment results of the inversion period in the target area with the course intensity weight set of each physical education course, and then generate a ranking table of each physical education course based on the output of the course duration decision model.
[0057] The physical education course data processing device provided in this application embodiment can execute the physical education course data processing method provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects of executing the method.
[0058] From a hardware perspective, to enable the implementation of the aforementioned physical education course data processing method in a computer, this application also provides an electronic device; please refer to [link to relevant documentation]. Figure 5 As shown, it is a schematic diagram of the structure of the electronic device described in this application, including: The system comprises a processor 1, a memory 2, a communication interface 3, and a bus 4; wherein the processor 1 and the memory 2, and the memory 2 and the communication interface 3, transmit data via the bus 4; the processor is used to process data in the memory and generate commands, the memory is used to store data, the communication interface is used to receive and send data, and the bus is used to realize data transmission between the processor, the memory, and the communication interface.
[0059] In this embodiment, the physical education course data processing method can be implemented as a runnable computer program. When the computer program is loaded into the processor or into the memory and processed by the processor via the bus, one or more steps of the physical education course data processing method can be executed.
[0060] This embodiment also provides a computer-readable storage medium for storing the computer-executable instructions. The computer-readable storage medium is a tangible physical storage medium that can store the computer program and various types of data used in the program. The physical storage medium includes, but is not limited to, existing physical storage media or combinations thereof, such as random access memory, read-only memory, optical disk, and hard disk.
[0061] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.
Claims
1. A method for processing physical education course data, characterized in that, include: Collect environmental data and course information for the target area; The intensity of each course is judged based on the course information, and the course intensity weight set of each physical education course is set based on the judgment results of the intensity of each course. An environmental inversion model is established based on environmental data of the target area, and then the inversion period of the target area is determined by the environmental inversion model. The radiation fluctuation state of the target area is assessed, and the environmental inversion model is updated based on the assessment results. A course duration decision model is established by combining the judgment results of the temperature inversion period in the target area with the course intensity weight set of each physical education course, and then the output results of the course duration decision model are used to generate a ranking table of each physical education course.
2. The physical education course data processing method according to claim 1, characterized in that, The expression for the intensity index of physical education courses is as follows: A(i) = a1 × α(i) + a2 × β(i); μ(i) = α(i) / β(i); In the formula, α(i) is the aerobic ratio index of the i-th physical education course, β(i) represents the anaerobic ratio index of the i-th physical education course, A(i) represents the intensity index of the i-th physical education course, μ(i) represents the intensity index of the i-th physical education course, and a1 and a2 are the aerobic intensity weight and anaerobic intensity weight, respectively.
3. The physical education course data processing method according to claim 2, characterized in that, The intensity index of physical education courses is numerically determined by setting a gradient intensity threshold and a course category proportion constant K, so as to classify each physical education course into different types. The process of categorizing the data from each physical education course is as follows: When μ(i) is less than K, the physical education course is classified as an endurance training course, and the environmental weight of the physical education course is set to exp{|μ(i)-K|}; otherwise, the physical education course is classified as a strength training course, and the environmental weight of the physical education course is set to 1; where K represents the course category ratio constant. When A(i) belongs to the Nth intensity interval, the course intensity weight of the physical education course is set as the product of exp[-1 / N] and the environmental weight of the physical education course.
4. The physical education course data processing method according to claim 3, characterized in that, Obtain a topographic map of the target area and its surface temperature. Based on the topographic map and surface temperature, construct a topographic radiation temperature space surface. Mark the coordinates of each location within the target area on the topographic map of the target area, and assign temperature values to each location coordinate using the surface temperature on the topographic map of the target area. Construct an initial topographic radiation temperature space surface based on the assignment results.
5. The physical education course data processing method according to claim 4, characterized in that, The temperature flow vector at each position coordinate is calculated based on the marking results, and the temperature flow vector at the j-th position coordinate is denoted as b(j). b(j) is defined as the sum of the vectors from the adjacent position coordinates to the j-th position coordinate, where j is the numerical subscript of the position coordinate. Then, the temperature inversion index γ(j) at each position coordinate is calculated by combining the temperature flow vector at each position coordinate with the temperature at each position coordinate. In the formula, bθ(j) represents the angle of the temperature flow vector at the j-th position relative to the ground plane, and B represents the standard value of change. The product of the temperature at the j-th location coordinate, the inversion temperature change index γ(j) at the j-th location coordinate, and the time interval G is used as the predicted topographic radiation temperature spatial surface for each time period.
6. The physical education course data processing method according to claim 5, characterized in that, Based on the predicted topographic radiation temperature spatial surface of the target area for each time period, the inversion layer thickness and temperature for each time period are obtained. When the inversion layer thickness is less than the inversion layer thickness threshold Q in the k-th time period, the time period is defined as an inversion time period. When the inversion layer thickness is greater than or equal to the inversion layer thickness threshold Q and the inversion layer temperature is greater than T in the k-th time period, the time period is defined as the top inversion time period. When the inversion layer thickness is greater than or equal to the inversion layer thickness threshold Q and the inversion layer temperature is less than or equal to T in the k-th time period, the time period is defined as the bottom inversion time period. T is the temperature for dividing the time period.
7. The physical education course data processing method according to claim 6, characterized in that, The surface thermal radiation intensity at each location is collected based on the topographic map of the target area; Calculate the radiation intensity weight W(j) for each location coordinate, and set W(j) = {HB(j) - min{HB(j)}} / {cos[bθ(j)] × L}; where HB(j) represents the altitude of the j-th location coordinate, and L is the longest slope length of the target area; The product of the radiation intensity weight of each location coordinate and the surface thermal radiation intensity of the corresponding location coordinate is used as the radiation intensity index of each location coordinate. A radiation intensity threshold is set. When the radiation intensity index of the j-th location coordinate is greater than or equal to the radiation intensity threshold, the inversion temperature change index of the j-th location coordinate is updated to γr(j).
8. The physical education course data processing method according to claim 7, characterized in that, When the i-th physical education course is an endurance training course, the inversion period is selected as the course period of the i-th physical education course, and the course duration of the physical education course is set to KT1(i). The value of KT1(i) is the product of the ratio of the baseline duration to the course intensity weight of the i-th physical education course and the temperature offset ratio of the target area of the k-th time period relative to T. When the i-th physical education course is a strength training course, the top time period of the temperature inversion is selected as the course time period of the i-th physical education course, and the course duration of the physical education course is set to KT3(i). The value of KT3(i) is set to be the ratio of η times the base duration to the course intensity weight of the i-th physical education course. A ranking table of physical education courses is generated based on the course duration and time slot of each course.
9. A physical education course data processing device, applied to the physical education course data processing method as described in any one of claims 1-8, characterized in that, include: The data acquisition unit is used to collect sports data of the target users, as well as environmental data and course information of the target area; The intensity weight setting unit is used to judge the intensity of each course based on the course information, and to set the course intensity weight set of each physical education course based on the judgment results of the intensity of each course. The temperature inversion analysis unit is used to establish an environmental temperature inversion model based on the environmental data of the target area, and then use the environmental temperature inversion model to determine the temperature inversion period of the target area. The inversion update unit is used to determine the radiation fluctuation state of the target area and update the environmental inversion model based on the determination result. The decision generation unit is used to establish a course duration decision model by combining the judgment results of the inversion period in the target area with the course intensity weight set of each physical education course, and then generate a ranking table of each physical education course based on the output of the course duration decision model.
10. An electronic device, characterized in that, The electronic device includes: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the physical education course data processing method according to any one of claims 1-8.