خلاصة:
Background. International successes, especially in the Olympic Games, have become significantly important to many countries. Hence, the prediction can be better planning to gain this goal.
Objectives. This study was conducted to predict the success of the participating countries in the Tokyo Olympic Games and this it was done using smart methods.
Methods. This study was conducted in two stages of qualitative (determination of indicators) and quantitative (collecting data on selected countries). In the first stage of the research, through a study of research background and collecting of library data, a preliminary list of predictive indicators was identified. In the next step, semi-structured and in-depth qualitative interviews as non-random purposive were conducted with four elites aware of the subject of the research. The discussions continued until theoretical saturation.
Results. According to the results of the research, the United States, China, and England will be ranked first to third in these games. The Islamic Republic of Iran will also be ranked 21 among the participating teams. Also, the coefficients of the predictive indicators of the rank of the countries participating in the Tokyo 2020 Olympic Games were calculated. Olympic Hosting. GDP per capita and the unemployment rate had the highest share in predicting countries, with 24.15%, 10.04% and 9.74%, respectively.
Conclusion. Using the theoretical model (PEST+S) and the neural network model, the countries’ sports policymakers were enabled to use the identified indicators and components in their future planning to successfully participate in the Olympics Games
ملخص الجهاز:
Predicting the Medals of the Countries Participating in the Tokyo 2020 Olympic Games Using the Test of Networks of Multilayer Perceptron (MLP) 1Pouya Fazlollahi, 1Akbar Afarineshkhaki*, 1Reza Nikbakhsh 1Department of Sports Science, Islamic Azad University, South Tehran Branch, Tehran, Iran.
com Predicting the Medals of the Countries Participating in the Tokyo 2020 Olympic Games As it’s obvious, the success of an athlete, team or delegation to a large extent depends on the functional capacity of the national system and its effectiveness in using all appropriate and relevant resources (5).
In this study, data from 195 countries were collected on three predictor variables and in their investigation, they concluded that the neural network model is a better tool than the regression model to predict countries’ success in the Olympic Games.
So the researcher is using a data mining tool of Artificial Neural Networks to answer the question of what is the estimated ranking of the countries participating in the Tokyo 2020 Olympic Games.
The conceptual pattern of research Predicting the Medals of the Countries Participating in the Tokyo 2020 Olympic Games Table 2.
The number of medals obtained and the ranking of each of the countries at the 2008 Olympics, along with the values predicted by the model used in this study are shown in Table 8.
The ranking and the number of medals obtained at the 2012 Olympics by the countries studied, along with the values predicted by the neural network model is reported in Table 9.