LSHADE with semi-parameter adaptation for chaotic time series prediction
Ni Tian, Lei Wang, Qiaoyong Jiang, Jinwei Zhao, Zhiqiang Zhao · 2018
In the field of nonlinear dynamical system, chaotic time series prediction is an important research area. In this paper, an enhanced differential evolution algorithm is adopted as the learning algorithm of MLP neural network to solve the chaotic time series prediction. To verify the performance of this approach, the numerical experiment on a typical chaotic time series prediction problem is executed. The experimental results confirm the superiority of the proposed method.