Abstract
Knowledge engineering offers substantial opportunities for integrating and managing conflicting demands in greenhouse crop production. A fuzzy inference system was developed to balance conflicting requirements of producing a high-quality, single-stem rose crop while simultaneously controlling production costs of heating and ventilation. An adaptive neuro-fuzzy inference system was built to predict the rose status of `Lady Diana' single-stem roses from nondestructive measurements. The fuzzy inference system was capable of making a critical decision based on the principle of economic optimization. Temperature set points for two greenhouses with similar rose status were treated significantly different by the fuzzy inference system due to differences in greenhouse energy consumption. Moderate reduction in heating energy costs could be realized with the fuzzy inference system.
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