The payload of drones in UAV networks is limited, making effective resource allocation essential for the networks. This paper explores UAV networks from the perspective of energy efficiency and formulates a multi-objective optimization problem to balance energy efficiency. We employ the Weighted Chebyshev method and Deep Deterministic Policy Gradients (DDPG) method to address this. Furthermore, we compare and evaluate these two methods, taking into account their anti-interference effects. Simulation results demonstrate the outstanding performance of the proposed algorithms.