Assessment of Happiness Measurement: A critical review - investigation of existing happiness measurement tools

Abstract

With the development of Olympic events, countries hope to achieve good results in these events by investing their efforts effectively. Therefore, it has become particularly important to explore the relationships among Olympic events, athletes, and other relevant factors. We developed a prediction model for the total number of medals for each country. It was found that countries like the United States and China will get the largest number of medals, and countries like France will get more medals in the next Olympics. Then, we built a BP Neural Network Model to predict the countries that can win the first medal in the Olympics. We found that countries such as Andorra and Bolivia have a probability of 0.35 and 0.32, respectively, of winning their first medal. The indicators, such as the accuracy rate of the model, all reach above 0.94, showing good prediction results. Furthermore, by further considering the number and types of sports events and the advantageous events, and using methods such as the independent sample T-test for analysis, we found that six countries, including China, have their advantageous events, such as table tennis. At the same time, the status of the host country also has an important impact on the medal distribution. We still analyzed the impact of introducing excellent coaches on sports performance. We found that China, the United States, and Romania need to introduce coaches in football, archery, and track and field events, respectively, to effectively improve their performance. Through further analysis, we obtained some other insights on the number of Olympic medals. First, we used the Random Forest Algorithm to analyze the correlation between the number of medals of each country and sports events. Then, we analyzed the gender ratio of athletes. Finally, by calculating the medal proportion of each country in different events, we identified the events with the least competition. The insights can help the National Olympic Committees optimize their Olympic strategies, allocate resources reasonably, and make breakthroughs in events with less competition. Finally, we conducted a sensitivity analysis and evaluated the advantages and disadvantages of the model. After analysis and verification, our model is not sensitive to parameter changes, is relatively stable, and has certain practical significance.