The organization of masses’ spontaneous sports activities based on BP neural network model

Abstract

Chinese government has made huge efforts in improving people’s spiritual and cultural life, but effects are far from satisfactory. The organization of masses’ spontaneous sports activities is the basic countermeasure to improve this situation, for it can not only reduce the government economic investment, but also meet the needs of people’s physical exercises. This paper takes five parks – Sunrise Park, Temple of Heaven Park, Beihai Park, Yu Yuantan Park and Purple Bamboo Park – in Beijing city as research objects, and makes the research on the current developing situations of the organization of masses’ spontaneous sports activities. Based on BP neural network model, the paper makes analysis according to the masses’ weekly exercises frequency and duration in the above-mentioned five parks. The results show that the organization of masses’ spontaneous sports activities in Temple of Heaven Park and Beihai Park is going quite well, while the situation of Sunrise Park and Purple Bamboo Park is far from that good.

Keywords

Masses organization of spontaneous sports activities BP neural network

1. Introduction

The organization of masses’ spontaneous sports activities is a part of non-governmental sports organizations, it is to meet people’s sports needs in a certain area and voluntary combination of social groups. With the improvement of people’s living standards, spontaneous mass sports activities have attracted more and more attention.

And to see the research significance of the paper, in recent years, with the improvement of people material standard of living, people’s demand on physical health and spiritual enjoyment also increasingly gets higher. Therefore, no matter in big cities or small towns, the organizations of masses’ spontaneous sports activities are becoming increasing crucial, and its development level directly affects people’s living quality. Combined with BP neural network model, the research in this paper can not only find out the running state of each evaluated park, but also it can throw light on the future development of organization of masses’ spontaneous sports activities. Combined with the characteristics of BP, this paper creatively introduces the BP neural network model into this study, and through the data analysis, in order to accurately reveal the actual operation of the five evaluation parks’ mass spontaneous sports activities.

2. Literature review

According to the existing literature, there are many scholars have studied the organization of masses’ spontaneous sports activities, from the research results, it mainly includes:

(1) The function of mass spontaneous sports activities development

About the function of mass spontaneous sports activities development, Zhao highlighted masses’ spontaneous sports activities to be one of important components of basic sports activities, which had positive effects on promoting local social cultures, people’s living quality and economic levels [1, 2].

From the theoretical perspectives of sociology and psychology, Song highlighted that the reason why masses’ spontaneous sports activities come into being is due to government’s insufficient investment in public sports activities. Meanwhile [3, 4], the author looked back on the development process, organizational status, characteristics and development trends of masses’ sports activities in China since the reform and opening up, and make interpretations of the emergence and development of masses’ spontaneous sports activities, he thought the spontaneous sports activity organization is an important supplement to large-scale sports organizations, and it has more important functions for people’s physical and mental health than large-scale sports organizations organized by the government.

(2) The main dilemma factors of mass spontaneous sports activities development

In this research area, Li took Jiaozuo city’s organization of mass spontaneous sports activities as research objects with multiple research methods [5]. The research results showed that there are a large number of masses’ spontaneous sports activities in small towns of Jiaozuo, Henan Province, which are mainly small and medium-sized with 30–100 people. The proportion of involved men and women is not balanced, and the overall education level is lower; On the other hand, the activities are mainly organized by individual sports events. Though the people in charge have a higher education background and financial resources, but they tend to be aging. Moreover, most of the activities do not have professional sports guiders, nor the fixed daily office sites; But the sites for activities are relatively fixed and spacious, which can basically meet the development needs of masses’ spontaneous sports activities.

As for the funds of the organization of activities, they are mainly from memberships’ fees of every activity, and the proportion of funds used for venues and equipment is relatively high. Though the organization of each activity could operate well, there still existed some problems, such as, the mechanism of organization and management is not sound, and the financial revenue and expenditure are not clear; Fund sources were not sufficient, there were no professional sports instructors; The supervision from higher-level departments was in sufficient. Therefore, the author pointed out that departments at all levels should strengthen their supervision force in the organization of masses’ spontaneous sports activities, and establish overall sports organization system; Besides, the organizer of every sports should establish guiding backbone teams, and the local government should encourage masses to spontaneously organize sports activities.

In addition, Zhang took Baoji county region league football associations as investigation objects, and respectively made analysis on the formation, maintenance and development of the masses’ spontaneous sports activity of the football league in Baoji county from the theoretical perspective of relevant economics, sociology and social psychology [6]. Finally, the analyzing results showed that the main factors restricting the development of masses’ spontaneous sports activities in urban communities in China are as follows: The organization and management system of masses’ sports activities is not sound; The managerial leadership and management consciousness are weak. Owing to the above analysis, it is important to put forward the following measures: taking social media as the platform, vigorously publicizing masses’ sports activities, strengthening the research and development ability in the organization of masses’ sports activities, and forming a management system of masses’ sports activities suitable for China’s national conditions [7].

(3) The essential conditions of mass spontaneous sports activities development

Based on the existing literature [8, 9, 10], according to the general laws of the formation, maintenance and development of the organization of masses’ spontaneous sports activities, it can be considered that the high level of sports technology, enthusiasm for serving the public spirit, adequate sports needs and suitable venues are the essential conditions of the organization of masses’ spontaneous sports activities [11, 12], and have made many strategies for mass spontaneous sports activities development [9, 10].

Based on the above-mentioned researches, this paper, to take five parks – Sunrise Park, Temple of Heaven Park, Beihai Park, Yu Yuantan Park and Purple Bamboo Park – in Beijing city as research objects, and to make research on the current developing situations of the organization of masses’ spontaneous sports activities.

3. Data collection and processing

The sound development of the organization of masses’ spontaneous sports activities can be mainly reflected in two aspects: to begin with the number of daily exercises of the participants in each spontaneous sports activity, the longer the time is, the better the development gets [13, 14]; Second, in terms of the number of weekly exercises of the participants in each spontaneous sports activity, better development can be got with more times for exercises. The model discussed in this paper will be used to evaluate the developing tendency of the organization of masses’ spontaneous sports activities in Sunrise Park, Temple of Heaven Park, Beihai Park, Yu Yuantan Park and Purple Bamboo Park, which can throw light on the future research and practices in the organization of masses’ spontaneous sports activities.

3.1 Data collection of evaluated parks

From the main characteristics of spontaneous sports organizations compared with official government organizations, the spontaneous sports organizations have the characteristics of organization, non-profit, autonomy and voluntariness, looseness and cohesion, the combination of virtual reality and boundary fuzziness, cultural communication and diversity of activities.

For this paper, the data are respectively from five parks in Beijing City (Sunrise park, Temple of Heaven Park, Beihai Park, Yu Yuantan Park and Purple Bamboo Park). In each park, the participants in different spontaneous sports activities were randomly selected. The selected participants finished the questionnaire about duration and frequency of their daily and weekly morning-exercise. What’s more, the recovery rate and effective rate of the questionnaire were ensured to be 100%. According to the survey, statistical data of duration in activities can be seen in Table 1, and the data about their weekly exercising frequency are sorted out in Table 2, and the value in the last line is the target value to be solved.

Table 1
The selected participants’ daily exercising duration (min) in masses’ spontaneous sports activities in different parks

Sunrise Park	Temple of Heaven Park	Beihai Park	Yu Yuantan Park	Purple Bamboo Park
30	50	60	50	60
30	60	50	40	80
50	90	90	60	50
60	80	80	80	90
90	90	70	40	40
60	90	40	60	80
40	80	60	50	50
60	60	90	50	60
45	45	80	30	40
30	60	60	40	30
50	90	80	60	50
30	50	90	40	60
60	80	60	70	40
90	50	30	60	30
45	30	40	80	30
51.33	67.00	65.33	54.00	52.67

From Table 1, it can be seen that participants’ daily exercising duration in Temple of Heaven Park and Beihai Park is longer, while it is shorter in Sunrise Park, Yu Yuantan Park as well as Purple Bamboo Park. The conclusion is a preliminary conclusion, as defined in the last line (average value for each item).

The selected participants’ weekly exercising frequency (times) in masses’ spontaneous sports activities in different parks.

Table 2

Data collection of featured values

Sunrise Park	Temple of Heaven Park	Beihai Park	Yu Yuantan Park	Purple Bamboo Park
5	7	4	3	5
6	7	5	4	2
4	6	6	2	4
4	5	7	3	6
3	7	5	5	3
7	6	5	7	1
2	5	6	4	3
2	4	6	3	2
4	5	5	5	3
5	3	5	4	5
2	5	6	6	5
4	6	5	7	7
6	4	4	5	3
3	3	2	4	2
2	3	3	2	3
3.93	5.07	4.93	4.27	3.60

In Table 2, the last line is the average value of each item, which is used as the basis for evaluation.

Five parks were divided into two categories according to the evaluation of the organization in masses’ spontaneous sports activities; That is, the parks went well in the organization of masses’ spontaneous sports activities, and the parks went poorly in the organization of masses’ spontaneous sports activities. In order to get the data of featured values, the data from some neighborhood committees were selected as the base, and statistical data can be got through sorting, which can be seen in Tables 3 and 4.

Table 3

Poor organization of masses’ spontaneous sports activities

Participants’ daily exercising duration (min) in masses’ spontaneous	30	50	40	45	35	40	45	50
sports activities
Participants’ daily exercising weekly frequency (times) in masses’	5	3	2	4	4	3	3	2
spontaneous sports activities

Table 4

Good organization of masses’ spontaneous sports activities

Participants’ daily exercising duration (min) in masses’ spontaneous	50	60	90	60	70	60	90	80
sports activities
Participants’ daily exercising weekly frequency (times) in masses’	7	5	7	6	5	7	6	5
spontaneous sports activities

In Tables 3 and 4, the advantage in good origination in masses’ spontaneous sports activities was not clearly illustrated. However, the data in Tables 3 and 4 can be used as the featured value of the BP neural network model to determine the evaluation object.

4. BP neural network model

4.1 Concept of neural network model

Neural network model is originated from neurobiology. Its computation process is similar to biology nerve cell reaction process in Fig. 1.

Figure 1.

The structure of neurons.

In neural networks, many different nerve cells, including axon terminals, can enter the dendrites of the same nerve cell and form a large number of synapses. All the neurotransmitters released from different synapses can act on the changes of membrane potential of the same nerve cell [15, 16]. Therefore, the ability of neural cells to synthesize information in space means that they can integrate the input information from different sources in dendrites [17, 18]. Based on the above-mentioned, the artificial neural cell model is established by simulating the reaction process of neural cells, as shown in Fig. 2, and the symbol definition in Fig. 2 is shown in Table 5.

Figure 2.

The schematic diagram of mathematical models for neurons.

Table 5

Mathematical model of symbol definition

Symbol	Definition
$x_{1},x_{2},\cdots,x_{n}$	The nerve cell input part is the information released by the upper level
$\theta_{i}$	Nerve cell threshold value
$y_{i}$	Nerve cell output
$f[{u_{1}}]$	Excitation function

Among them, $f[{u_{1}}]$ decides that output form that arrives at threshold value $\theta_{i}$ under common effects of inputting $x_{1},x_{2},\cdots,x_{n}$ . Figure 3 shows two kinds of excitation functions images. The paper adopted models uses the second kind of excitation function.

Figure 3.

Typical excitation functions.

Among them:

$\displaystyle u_{i}=\sum\limits_{j}w_{ij}x_{i}-\theta_{i}$ (1)

So:

$\displaystyle y_{i}=f[{u_{i}}]=f\left({\sum\limits_{j}{w_{ij}-\theta_{i}}}\right)$ (2)

Equation (2) is the complete expression of a mathematical model of individual nerve cells.

4.2 Calculation steps in BP neural network model

BP neural network is a kind of multiple-layer feed forward network, and adopts minimum mean square error computational method. When applying the back propagation algorithm into feed forward multiple-layer networks, Sigmoid is utilized as excitation function, and the network weight coefficient $w_{ij}$ can be recursively figured out following the steps. In case every layer has several nerve cells, for the $i$ nerve cell in the $k$ layer, it has $n$ pieces of weight coefficients $w_{i1},w_{i2},\cdots,w_{jn}$ . In addition, select one more $w_{jn+1}$ to express $\theta_{i}$ , input sample $x$ , and assume $x=({x_{1},x_{2},\cdots,x_{n},1})$ . If each layer has several nerve cells, then for each layer, it has several weight coefficients.

⟀ Align value to $w_{ij}$ . To every layer $w_{ij}$ , align is a very little nonzero random number, and meanwhile $w_{jn+1}=-\theta_{i}$ . Since the model is operated by MATLAB, the alignment process is a random process of the computer. Therefore, the results of the same programming code may be different in different running processes.

⟁ Input sample value $x=({x_{1},x_{2},\cdots,x_{n},1})$ , and corresponding expected output $y=(y_{1},y_{2},\cdots,\linebreak y_{n},1)$ .

⟂ Calculate each layer’s output; Then for the $k$ layer the $i$ nerve cell’s output $x_{ik}$ is as the following:

$\displaystyle y_{i}^{k}=f[{u_{i}^{k}}]$ (3)

Among them,

$\displaystyle u_{i}^{k}=\sum\limits_{j}{w_{ij}x_{j}^{k-1}}-\theta_{i}^{k}$ (4)

In formula, $x_{n+1}^{k-1}=1$ , $w_{i({n+1})}=-\theta$ .

⟃ Solve each layer’s computation error $d_{i}^{k}$ , for the output layer, it has $k=m$ , then it has:

$\displaystyle d_{i}^{m}=x_{i}^{m}({1-x_{i}^{m}})({x_{i}^{m}-y_{i}^{m}})$ (5)

For other layers, it has:

$\displaystyle d_{i}^{k}=x_{i}^{k}({1-x_{i}^{k}})\left({\sum\limits_{j}{w_{ij}x% _{j}^{k-1}-\theta_{i}^{k}}}\right)$ (6)

⟄ Correct $w_{ij}$ and $\theta_{i}$ , it has:

$\displaystyle w_{ij}({t+1})=w_{ij}(t)-\eta d_{i}^{k}x_{j}^{k-1}$ (7)

⟅ After figuring out each layer’s weight coefficient, it can judge whether it conforms to requirements according to the established criterion. If it does so, the computation is finished; If not, then return to step ⟂.

Figure 4.

Distribution of two indicators of the organization in sports activities.

4.3 MATLAB computation and computed results

When the program code MATLAB is running, the selective training error $10^{-2}$ of the program is used as the condition to stop the calculation. Since the data of participants’ daily exercising duration and weekly frequency in masses’ spontaneous sports activities are both between 0–100, it is proper to select the stop calculation condition. In the following schematic diagram, “*” represents the parks running well in the organization of masses’ spontaneous activities, and “o” represents the parks running poorly in the organization of masses’ spontaneous activities [19].

In Tables 3 and 4, two kinds of featured values in the organization of masses’ spontaneous activities are illustrated. Consequently, MATLAB can be utilized to draw two kinds of distribution state of the organization in sports activities, which can be seen in Fig. 4. According to the distribution state of Fig. 4, the discrimination line is defined, and then the diagram for discrimination results is defined, as shown in Fig. 5.

From the distribution state in Fig. 4, it can be seen there are obvious borders between the two kinds of organization in sports activities; Therefore, discriminant straight line (45, 7) and (65, 2) can be defined. Figure 5 shows the schematic diagram of discrimination results.

Figure 5.

The schematic diagram of discrimination results.

According to Fig. 5, it is clear that the organization of masses’ sports activities in Temple of Heaven Park, Beihai Park went well, while the organization of masses’ sports activities in other three parks went was not sound; Moreover, the situation in Sunrise Park and Purple Bamboo Park was the worst. In fact, Sunrise Park is located in the middle of the Sunrise District. Although the traffic there is developed, there are many office buildings nearby, and the nearby residents are mostly office workers, who are busy with work; Hence, few of them have carried out long-term plan for masses’ sports activities. On the other hand, Temple of Heaven Park and Beihai Park lie in the old Beijing urban districts, but the number of residents nearby participating in the sports is relatively large.

5. Conclusion

This paper, to apply BP neural network model in evaluating the organization of masses’ spontaneous sports activities, and makes analysis on the five parks – Sunrise Park, Temple of Heaven Park, Beihai Park, Yu Yuantan Park and Purple Bamboo Park. BP Neural network can not only realize the reflection process from input information to output result, but also has the ability to deal with many kinds of input information, making complex problems easier to solve and process.

And the results show that the organization of masses’ sports activities in Temple of Heaven Park, Beihai Park went well, while the organization of masses’ sports activities in other three parks was not sound; Moreover, the situation in Sunrise Park and Purple Bamboo Park was the worst. Combined with practical conditions, it can be found that the research results are reasonable about the status of the five parks in Beijing, China.

Footnotes

Acknowledgments

The authors would like to give sincere thanks to the Project in Philosophy and Social Science Fund of Shandong Province (15CTY09). And the authors gratefully acknowledge the reviewers of this paper for their helpful comments and suggestions.

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The organization of masses’ spontaneous sports activities based on BP neural network model

Abstract

Keywords

1. Introduction

2. Literature review

(1) The function of mass spontaneous sports activities development

(2) The main dilemma factors of mass spontaneous sports activities development

(3) The essential conditions of mass spontaneous sports activities development

3. Data collection and processing

3.1 Data collection of evaluated parks

Table 1 The selected participants’ daily exercising duration (min) in masses’ spontaneous sports activities in different parks

4.1 Concept of neural network model

Footnotes

Acknowledgments

References

Table 1
The selected participants’ daily exercising duration (min) in masses’ spontaneous sports activities in different parks