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New and less energy consuming methods are developed to reduce the increasing heating costs day by day. Heat transfer method is one of the most commonly used methods for heating an environment. The amount of heat required to heat an environment in a heat transfer technique is found by the amount of heat lost from the environment. In this study, artificial neural networks were used for estimating the monthly heat demand for the heating needs of a greenhouse in Elazığ province with 2017 meteorological and spatial data. The amount of heating has been tried to be estimated using the MATLAB program with the lowest error. Heating Degree-Day (HDD) values and latitude, longitude and altitude data were used for analyzes to be made in the artificial neural network model. It has been estimated that the heat requirement for the heating of the greenhouse is lower than the heat requirement for the heat transfer method in the designed artificial neural network model.The artificial neural networks model has been found to be a useful method for studying the heating of greenhouses.
International Conference on Advanced Technologies, Computer Engineering and Science
ICATCES
Özlem Alpay
Ebubekir Erdem