ABSTRACT
BACKGROUND: The Ultimate Fighting Championship (UFC) stands as a prominent global platform for professional mixed martial arts, captivating audiences worldwide. With its continuous growth and globalization efforts, UFC events have garnered significant attention and achieved commendable results. However, as the scale of development expands, the operational demands on UFC events intensify. At its core, UFC thrives on the exceptional performances of its athletes, which serve as the primary allure for audiences. OBJECTIVE: This study aims to enhance the allure of UFC matches and cultivate exceptional athletes by predicting athlete performance on the field. To achieve this, a recurrent neural network prediction model based on Bidirectional Long Short-Term Memory (BiLSTM) is proposed. The model seeks to leverage athlete portraits and characteristics for performance prediction. METHODS: The proposed methodology involves constructing athlete portraits and analyzing athlete characteristics to develop the prediction model. The BiLSTM-based recurrent neural network is utilized for its ability to capture temporal dependencies in sequential data. The model's performance is assessed through experimental analysis. RESULTS: Experimental results demonstrate that the athlete performance prediction model achieved an overall accuracy of 0.7524. Comparative analysis reveals that the proposed BiLSTM model outperforms traditional methods such as Linear Regression and Multilayer Perceptron (MLP), showcasing superior prediction accuracy. CONCLUSION: This study introduces a novel approach to predicting athlete performance in UFC matches using a BiLSTM-based recurrent neural network. By leveraging athlete portraits and characteristics, the proposed model offers improved accuracy compared to classical methods. Enhancing the predictive capabilities in UFC not only enriches the viewing experience but also contributes to the development of exceptional athletes in the sport.
ABSTRACT
OBJECTIVE: High altitude hypoxic environment has a certain negative impact on physical fitness of adolescents. We aimed to understand the physical fitness status of Tibetan adolescents in different high-altitude areas in Tibet, China. METHODS: Physical fitness items, such as grip strength, standing long jump, sit and reach, 50 m dash, 1000 m run for boys, and 800 m run for girls were tested on 3806 Tibetan adolescents by using stratified whole group sampling method in class units. The mean age of the participants was (15.51 ± 1.69) years for Tibetan males and (15.54 ± 1.69) years for females. One-way analysis of variance (ANOVA) and other methods were used to make cross-sectional comparisons of physical fitness performance of Chinese Tibetan adolescents in different high-altitude regions. RESULTS: The standing long jump scores of boys (203.37 ± 28.36) were higher than that of girls (152.97 ± 19.46) and the lowest standing long jump scores of adolescents in Shigatse region (166.39 ± 35.04). The highest level of sit and reach was found among boys (10.69 ± 5.34) in Nyingchi and the lowest level of sit and reach was found among girls (8.42 ± 5.84) in Shigatse. Shigatse region adolescents had the lowest performance in 50 m dash (9.09 ± 1.72) while the best performance in 1000 m run (266.23 ± 35.82) and 800 m run (245.40 ± 27.92). CONCLUSION: There is variability in the physical fitness of Tibetan adolescents in different high-altitude regions of Tibet, China. Targeted physical fitness interventions should be carried out for Tibetan adolescents in different high-altitude regions. The focus should be on improving the endurance quality of Tibetan adolescents in Lhasa and the lower limb muscle strength, flexibility, and speed quality of adolescents in Shigatse.
