Deep Elman Neural Network for Greenhouse Modeling

In this work, we propose to use recurrent deep learning method to model a complex system. We have chosen Deep Elman neural network with different structures and sigmoidal activation functions. The emphasis of the paper is to compare modeling results on a greenhouse and to demonstrate the abilities of Deep Elman neural network in a modeling step. For this, we used training and validation datasets. Simulation results proved the ability and the efficiency of Deep Elman neural network with two hidden layers.

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