Neuro-Fuzzy modeling of energy use in greenhouse strawberry production

Fatemeh Hosseini-Fashami¹ Ali Motevali² Ashkan Nabavi-Pelesaraei³ Seyed Jafar Hashemi⁴

1) M.Sc Student, Department of Mechanics of Biosystem Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
2) Assistant Professor, Department of Mechanics of Biosystem Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
3) PhD Graduated, Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran
4) Associated Professor, Department of Mechanics of Biosystem Engineering, Sari Agricultural Sciences and Natural Resources University, Sari, Iran

Publication : 4th.International Conference on Researches in Science & Engineering & International Congress on Civil, Architecture and Urbanism in Asia(4icrsie.com)
Abstract :
The aim of this study was to determine energy consumption and the relationship between energy input and output in greenhouse strawberry production using adaptive neuro-fuzzy inference system (ANFIS). Data used in this study were obtained from 30 randomly selected greenhouse strawberry producers using a face to face interview. The average energy consumption and yield were calculated as 922565.89 MJ ha-1 and 75062.50 kg ha-1, respectively. The results revealed that diesel fuel with 80% of total energy use were the main energy consuming inputs. Also, the energy forms results indicated non-renewable and direct energies was more than renewable and indirect energies, respectively. ANFIS model is developed based on a hybrid learning algorithm, with R2 for predicting output energy being 0.993. Results indicate that the multi-level ANFIS is a useful tool to managers for large-scale planning in forecasting energy output of agricultural production systems.
Keywords : Energy Modeling Strawberry ANFIS