A Design and Implementaion of Carry Distance Prediction Model using Artificial Neural Network - Ko, Jun Young; Kim, Kyeong Rok; Kim, Jae Hyun (9th International Conference on Information and Communication Technology Convergence: ICT Convergence Powered by Smart Intelligence, ICTC 2018, 2018)
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.
Keywords: Dependent variables; Golf balls; High frequency radar; Initial velocities; Input variables; Performance evaluations; Prediction model; Root mean square errors; Artificial Neural Network (ANN); golf ball carry distance; Root Mean Square Error (RMSE)