Time series predication based on genetic chaotic operators network

Scientifically prediction of some statistical data in practical production can guide mission planning and scheduling, policy-making and emergency treatment. A new dynamic prediction network is proposed to improve the prediction performance of conventional method. The prediction network is composed of many chaotic operators, and its control parameters are optimized by genetic algorithm. The dynamic characteristic of the network can be changed to follow that of the system predicted. The prediction results of actual data, such as passenger traffic, freight traffic, goods volume, and passenger volume, show that the method is valid, and it has good predictive ability and precision.