AN ALGORITHM OF CHAOTIC DYNAMIC ADAPTIVE LOCAL SEARCH METHOD FOR ELMAN NEURAL NETWORK

作者：Zhang Zhiqiang^*; Tang Zheng; Gao Shangce; Yang Gang

来源：International Journal of Innovative Computing Information and Control, 2011, 7(2): 647-656.

• Elman neural network (ENN)
• Sunspot-related time series prediction
• Adaptive local search (ALS)
• Chaotic dynamic

In this paper, we present an efficient algorithm for the prediction of sunspot-related time series, namely the Chaotic Dynamic Adaptive Local Search (CDALS) algorithm. This algorithm is based on exploiting partially recurrent Elman Neural Network (ENN) and it can be divided into two main steps: the first one is the basic model of the Adaptive Local Search (ALS) proposed in our previous work. After that, a hybrid local search method is proposed by introducing the chaos signals into ALS. Thus, ALS and chaos are hybridized to form a powerful CDALS algorithm, which reasonably combines the searching ability of ALS and chaotic searching behavior. Simulation results show that the CDALS algorithm can eventually reach the global optimum or its good approximation with high probability, effectively enhance the searching efficiency and quality within reasonable number of iterations.

• 出版日期2011-2