A Design and Implementaion of Carry Distance Prediction Model using Artificial Neural Network | IEEE Conference Publication | IEEE Xplore

A Design and Implementaion of Carry Distance Prediction Model using Artificial Neural Network


Abstract:

A golf shot pattern analyzer, which can derive a golf ball speed, a launch angle, and a spin, measures parameters using a high frequency radar or a high speed camera. But...Show More

Abstract:

A golf shot pattern analyzer, which can derive a golf ball speed, a launch angle, and a spin, measures parameters using a high frequency radar or a high speed camera. But it is difficult to measure a carry distance of golf ball moving several tens of meters. Therefore, the carry distance of golf ball is calculated by various variables such as an initial velocity of golf ball, a launch angle, a spin rate, etc. In this paper, we calculate the carry distance of golf ball based on an Artificial Neural Network (ANN). The ANN model uses five dependent variables (club speed, attack angle, golf ball speed, launch angle, and spin rate) as input variables. A structure of the ANN model consists of one input layer, four hidden layers, and one output layer. Hidden nodes of the hidden layer are composed of 10, 20, 20, and 20 nodes, respectively. A Root Mean Square Error (RMSE) is used for performance evaluation and the RMSE of the ANN model is 0.8.
Date of Conference: 17-19 October 2018
Date Added to IEEE Xplore: 18 November 2018
ISBN Information:
Print on Demand(PoD) ISSN: 2162-1233
Conference Location: Jeju, Korea (South)

References

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