Forecasting arabica coffee yields by auto-regressive integrated moving average and machine learning approaches
Yotsaphat Kittichotsatsawat,
Anuwat Boonprasope,
Erwin Rauch
et al.
Abstract:<abstract>
<p>Coffee is a major industrial crop that creates high economic value in Thailand and other countries worldwide. A lack of certainty in forecasting coffee production could lead to serious operation problems for business. Applying machine learning (ML) to coffee production is crucial since it can help in productivity prediction and increase prediction accuracy rate in response to customer demands. An ML technique of artificial neural network (ANN) model, and a statistical technique of aut… Show more
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