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Supervised machine learning is a promising technique to achieve joint resource allocation and selection of mobile relays in cooperative heterogeneous networks. Joint resource allocation and mobile relay selection are NP-hard problems in the sense that they cannot be solved in polynomial time. To solve this problem, highly complex heuristic solutions based on channel conditions and physical-layer parameters have been considered. Our research explores an artificial neural network (ANN) approach to the joint allocation of resources and choice of a mobile relay with efficient utilization of resources in terms of energy efficiency (EE) and spectral efficiency (SE). To this, there exists a tradeoff between the two, i.e., EE and SE, and to consider this tradeoff, a new metric resource efficiency (RE) has already been introduced in the literature. This article addresses the problem of learning a regression model for …