발간년도 : [2018]
| 논문정보 |
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| 논문명(한글) |
[Vol.13, No.5] A Study on Hadoop-based Self-Organizing Map for Golf Swing Model in Big Data Environment |
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| 논문투고자 |
Wansik An |
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| 논문내용 |
The healthcare and physical strength are critical factors to be considered in a highly competitive environment in human life. Many people prefer sport is designed to obtain the key of human life because it is a good characteristic both health and physical strength. One of the Golf Swing Model (GSM) in sport is defined as a designed, computer treated of complexity of motions automatically. Especially, GSM is apparently concerned with speed generation its adaptability such as golfer segment angular kinematics, kinetic energy and angular momentum. For this reason, the design of GSM is need to expertise on knowledge of motion patterns, improve by altering the sequence of rotations in the conventional golf swing. In our research paper, it is to study and evaluate the GSM by simulating modeling for experiment and analysis. The methodology used in our research is simulated by Self-Organizing Maps (SOM). SOM provide the design system as well as offer environment to which experiment of the system can be performing. Eventually, our GSM by using SOM is presented some researchable scenario. In addition, we extend the algorithm to handle attribute datasets containing both numeric and categorical attributes in Big Data Environment. |
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