time series prediction with a hybrid system formed by artificial neural network and cognitive development optimization algorithm

Time series prediction is a remarkable research interest, which is widely followed by scientists / researchers. because many fields include analyzing processes over such time series, different kinds of approaches, methods, and techniques are often employed in order to achieve alternative prediction ways. it seems that artificial intelligence oriented solutions have strong potential on providing effective and accurate prediction approaches in even most complicated time series structures. in the sense of the explanations, this study aims to introduce an alternative, artificial intelligence based approach of artificial neural networks, and cognitive development optimization algorithm, a recent intelligent optimization technique introduced by the authors. here, it has been aimed to predict different kinds of time series, by using the introduced system / approach. in this way it has been possible to discuss about application potential of the hybrid system and report findings related to its success on prediction. the authors believe that the study has been a good chance to support the literature with an alternative solution approach and see potential of a newly developed, artificial intelligence oriented optimization algorithm on different applications.