GREENHOUSE CONTROL BY MACHINE LEARNING

K. Kurata
This study aims at developing a system which learns grower's greenhouse control methods (rules) by measuring environmental factors, crop status, if possible, and grower's behavior and later the learned rules are applied to the automatic greenhouse control. In brief, the system imitates the grower. In this way, the grower will be released from the management labor without losing his own rules.

This report presents a learning algorism developed which is named K-algorism. Although K-algorism is a simple one, it has proved to be very powerful.

Kurata, K. (1988). GREENHOUSE CONTROL BY MACHINE LEARNING. Acta Hortic. 230, 195-200
DOI: 10.17660/ActaHortic.1988.230.23
https://doi.org/10.17660/ActaHortic.1988.230.23

Acta Horticulturae