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http://dx.doi.org/10.3745/KTSDE.2017.6.12.565

A Study on Prediction of Attendance in Korean Baseball League Using Artificial Neural Network  

Park, Jinuk (연세대학교 컴퓨터과학과)
Park, Sanghyun (연세대학교 컴퓨터과학과)
Publication Information
KIPS Transactions on Software and Data Engineering / v.6, no.12, 2017 , pp. 565-572 More about this Journal
Abstract
Traditional method for time series analysis, autoregressive integrated moving average (ARIMA) allows to mine significant patterns from the past observations using autocorrelation and to forecast future sequences. However, Korean baseball games do not have regular intervals to analyze relationship among the past attendance observations. To address this issue, we propose artificial neural network (ANN) based attendance prediction model using various measures including performance, team characteristics and social influences. We optimized ANNs using grid search to construct optimal model for regression problem. The evaluation shows that the optimal and ensemble model outperform the baseline model, linear regression model.
Keywords
Artificial Neural Network; Korean Baseball League; Attendance; Hyperparameter; Grid Search; MAPE;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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