Abstract:Extreme learning machine(ELM) is a new type of single feed layer neural network algorithm. In the training process ELM only needs to set the hidden layer node number of suitable, random set the input weights and hidden layer deviation, finish in one time without iteration. Now use the genetic algorithm to optimize the extreme learning machine to find the optimal parameter values, so as to establish the Chengdu Shuangliu International Airport passenger throughput prediction model. Then through the comparison of support vector machine, BP neural network, analysis the feasibility and advantage of genetic-extreme learning machine algorithm. The simulation results show that the genetic-extreme learning machine algorithm is not only feasible, and compared with the original extreme learning machine algorithm, it has obvious advantages in prediction accuracy and training speed.