Regression model for apple yield prediction

Shuna Zhang; Li Sun; Shuhan Cheng

doi:10.1117/12.2627618

22 April 2022 Regression model for apple yield prediction

Shuna Zhang, Li Sun, Shuhan Cheng

Proceedings Volume 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021); 121631K (2022) https://doi.org/10.1117/12.2627618
Event: International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 2021, Nanjing, China

Abstract

China is a large producer of apples, whose yield is influenced by climatic, socioeconomic, and other factors. It is therefore of great practical significance to thoroughly analyse the developmental trend of the apple industry. In this study, a linear regression model for 2005–2012, and a logistic regression model for 2012–2020, were established based on apple yield data from the National Bureau of Statistics. The numerical results showed that the prediction results were valid.

Citation Download Citation

Shuna Zhang, Li Sun, and Shuhan Cheng "Regression model for apple yield prediction", Proc. SPIE 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 121631K (22 April 2022); https://doi.org/10.1117/12.2627618

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