Modeling of Geothermal EAHE Outputs Using Convolutional Neural Network and Artificial Neural Network in Ghardaia

Abstract

Artificial Intelligence (AI) and thermal energy systems are two distinct fields and the role of both in advancing scientific research and supporting sustainable development, making this study saturated with knowledge diversity, where deep learning was exploited to optimise the performance of geothermal heat exchangers. A feed-forward back-propagation network and a convolutional neural network were used to use the data obtained in a specific period to build an accurate predictive model that helps optimise the system performance.