Predict Explanatory Power Through Autoregressive Functions and Fuzzy Time Series by Archery Performance.

Purpose: Predicted the explanatory power of core through the application of autoregressive functions and fuzzy time series by archery performance. Can the archery performance of different athletes (high-score group and low-score group) be predicated and evaluated? In this study, purposive sampling was used to recruit the research participants by Chinese Taipei Archery Association (CTAA) were data collected in this study. Method: This study applied fuzzy statistics to the analysis of quadratic regression, autoregressive functions, and transfer functions. Subsequently, these statistics and relevant data were analyzed using Minitab 16.0 and Microsoft Office Excel 2013. Results: The findings of this study are listed as follows: Using autoregressive functions and fuzzy time series can truly reflect the explanatory power of athletes' performance in archery and effectively predict the archery performance of male athletes in the high-score group during the 2013 Asian Games. Suggestion: Fuzzy mode could be used to investigate the academic performance and learning environment of universities because it enhances the authenticity of students learn skill. Further academic learn training programs for student could be planned according to contest goals and contents, and the proportion of male to female student can be determined according to current situations. Contribution: The performance of student predicted using fuzzy time series should be used to design training programs for athletes and to assess students' ability to participate in learn environment. [ABSTRACT FROM AUTHOR]