Artificial neural networks can offer the better solution to the passenger call distribution problem when compared to the conventional elevator control systems. Therefore, the application of neural networks in elevator group control system is discussed. The significance of introducing artificial neural networks is presented. Elevator group control systems with neural networks can predict the next stopping floors to stop by considering what has been learnt by processing the changes in passenger service demand pattern. This paper deals with the use of artificial neural networks for the distribution of the most suitable cars to the floors by considering the passenger service demand. Artificial neural networks are applied in Duplex/Triplex group control systems for improving passenger waiting time. The backpropagation algorithm is used for training neural networks. The elevator traffic analysis and simulation results are presented and compared to conventional elevator control systems. (C) 2008 Journal of Mechanical Engineering. All rights reserved.