Dynamic recurrent Elman neural network based on immune clonal selection algorithm

摘要

Owing to the immune clonal selection algorithm introduced into dynamic threshold strategy has better advantage onoptimizing multi-parameters, therefore a novel approach that the immune clonal selection algorithm introduced intodynamic threshold strategy, is used to optimize the dynamic recursion Elman neural network is proposed in the paper.The concrete structure of the recursion neural network, the connect weight and the initial values of the contact units etc.are done by evolving training and learning automatically. Thus it could realize to construct and design for dynamicrecursion Elman neural networks. It could provide a new effective approach for immune clonal selection algorithmoptimizing dynamic recursion neural networks.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.