基于进化RBF神经网络的非平稳时间序列分析

The Time Series Analysis Based on Evolutionary-RBF Neural Networks

针对非线性时间序列中的非平稳数据，本文结合差分平稳化和分阶遗传训练的方法，提出一种新的进化RBF神经网络结构及其学习算法。算例仿真结果显示，该算法在处理非平稳时间序列问题时具有一定的优越性。

： Combined with the methods of difference and hierarchical genetic algorithm, a novel model called Evolutionary RBF and its learning algorithm are presented to analyze the non-stationary data in the nonlinear time series. The simulation results confirm the superior performance of the Evolutionary RBF over the classical neural networks, and the former is more suitable to solve non-stationary time series problems.