Turf grass irrigation using neuro-fuzzy system

Abstract

Turf grass needs water to survive and stay green, but too much water can really damage it. Turf grass irrigation processes can lead to excess water consumption. The irrigation process is based on several factors, which are evapotranspiration rate, grass evapotranspiration rate and tensiometer reading. This study proposes an irrigation process system using Neuro-Fuzzy method that was experimented on real meteorology data. Both the backpropagation and resilient backpropagation were explored and compared. The system with the resilient backpropagation method has achieved higher accuracy rate compared to the backpropagation method with an average of 10% of reduction in water usage. © 2012 Springer-Verlag.