Korean Journal of Organic Agriculture (한국유기농업학회지)

Korean Association of Organic Agriculture (한국유기농업학회)
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Development of Yield Forecast Models for Vegetables Using Artificial Neural Networks: the Case of Chilli Pepper

인공 신경망을 이용한 채소 단수 예측 모형 개발: 고추를 중심으로

  • 이춘수 (단국대학교 환경자원경제학과) ;
  • 양성범 (단국대학교 환경자원경제학과)
  • Received : 2017.07.31
  • Accepted : 2017.08.21
  • Published : 2017.08.31
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Abstract

This study suggests the yield forecast model for chilli pepper using artificial neural network. For this, we select the most suitable network models for chilli pepper's yield and compare the predictive power with adaptive expectation model and panel model. The results show that the predictive power of artificial neural network with 5 weather input variables (temperature, precipitation, temperature range, humidity, sunshine amount) is higher than the alternative models. Implications for forecasting of yields are suggested at the end of this study.

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References

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