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

인경신경망을 이용한 한국프로야구 관중 수요 예측에 관한 연구

  • 박진욱 (연세대학교 컴퓨터과학과) ;
  • 박상현 (연세대학교 컴퓨터과학과)
  • Received : 2017.07.17
  • Accepted : 2017.08.17
  • Published : 2017.12.31

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.

Acknowledgement

Supported by : 한국연구재단

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