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Frost Forecasting System with Multiple Models of Machine Learning
Shugo Yoshida, Liya Ding, Kosuke Noborio, Kazuki Shibuya
117 - 122
10.3233/FAIA220433
Research Article
Frontiers in Artificial Intelligence and Applications
Volume 360: Machine Learning and Artificial Intelligence
Abstract

Frost causes damage to crops. Predicting the frost occurrence in advance is highly valuable for practitioners taking possible frost-prevention measures. In our previous study, we have applied machine learning to forecast frost occurrence using two methods. To better support user with a potential trend of frost occurrence in a future period, we propose an integrated system of frost forecast taking the advantages of the two methods.

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