Optimal use of energy is a key requirement for sustainable agriculture. However, the growing demand for food has increased the energy consumption of the agricultural sector. Since the agricultural sector is the main sector of energy conversion, we focused on evaluating the efficiency of cucumber greenhouses in East Azerbaijan Province by artificial neural network and ANFIS. So, 135 cucumber producing greenhouses were sampled, and data were collected with an interview questionnaire. Finally, the inputs and output energy, the energy indices and the energy consumption of cucumber greenhouse was assessed and modeled. Among the inputs, fuel and seed had the highest and lowest share of 55.37 and 23×10-5 % in total energy consumption, respectively. The results for the modeling of energy consumption revealed that R2 was 96, 87, 89, and 39.7% for RBF, MLP, ANFIS, respectively. So, RBF network could predict energy consumption of the greenhouses with the least error.
Ebrahimpour, Zahra; sharabiani, Vali; and Taghinezhad, Ebrahim
"Modeling of Energy Consumption of Cucumber Greenhouses Usingartificial Neural Network and ANFIS,"
Emirates Journal for Engineering Research: Vol. 24:
4, Article 7.
Available at: https://scholarworks.uaeu.ac.ae/ejer/vol24/iss4/7