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.

• 이춘수(단국대학교 환경자원경제학과 강사) | Lee, Choon-Soo
• 양성범(단국대학교 환경자원경제학과 조교수) | Yang, Sung-Bum Corresponding author