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Abstract. The 5th generation technologies, i.e. 5G based on a new flexible architecture named by Software Defined Network(SDN) technologies, which is adaptable to use cases and scenarios. SDN allows more flexible and dynamic network resource management that is becoming a key problem in 5G. To meet the needs of all kinds of traffics, the efficient resource allocation algorithm has been proposed which is of extreme importance for SDN. In this paper, the merit of quick converging to the global optimal solution was used to design the fitness function of the network resource management. The ability of fast random search of particle swarm optimization was used to realize the update and optimization. The simulation results show that can reduce the energy consumption of the network and improve the utilization rate of cyber source at the same time.

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In this paper, an application of the hybrid intelligent control algorithm to semi‐active control of the magnetorheological (MR) damper is presented for engineering structures. The control signal is optimized directly by the µGA approach to obtain the numerical relation between the control signal and the system output. This relation is then stored in the weight value of a trained artificial neural network, which can be available for another structure subjected to other seismic inputs. The results of a numerical example indicate that the semi‐active control of the MR damper based on the hybrid algorithm can efficiently reduce the structural responses induced by an earthquake. Copyright © 2007 John Wiley & Sons, Ltd.