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• W2022383869 abstract "The use of neural networks for time series prediction has been an important focus of recent research. Multi-objective optimization techniques have been used for training neural networks for time series prediction. Cooperative coevolution is an evolutionary computation method that decomposes the problem into subcomponents and has shown promising results for training neural networks. This paper presents a multi-objective cooperative coevolutionary method for training neural networks where the training data set is processed to obtain the different objectives for multi-objective evolutionary training of the neural network. We use different time lags as multi-objective criterion. The trained multi-objective neural network can give prediction of the original time series for preprocessed data sets distinguished by their time lags. The proposed method is able to outperform the conventional cooperative coevolutionary methods for training neural networks and also other methods from the literature on benchmark problems." @default.
• W2022383869 created "2016-06-24" @default.
• W2022383869 creator A5043246042 @default.
• W2022383869 creator A5045815994 @default.
• W2022383869 date "2014-07-01" @default.
• W2022383869 modified "2023-09-27" @default.
• W2022383869 title "Multi-objective cooperative coevolution of neural networks for time series prediction" @default.
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• W2022383869 doi "https://doi.org/10.1109/ijcnn.2014.6889442" @default.
• W2022383869 hasPublicationYear "2014" @default.
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