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Cooperative coevolution of Elman recurrent neural networks for chaotic time series prediction
TLDR
This work employs two problem decomposition methods for training Elman recurrent neural networks on chaotic time series prediction. Expand
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Competition and Collaboration in Cooperative Coevolution of Elman Recurrent Neural Networks for Time-Series Prediction
  • Rohitash Chandra
  • Computer Science, Medicine
  • IEEE Transactions on Neural Networks and Learning…
  • 5 March 2015
TLDR
This paper presents a competitive CC method for training recurrent neural networks for chaotic time-series prediction. Expand
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Competitive two-island cooperative coevolution for training Elman recurrent networks for time series prediction
  • Rohitash Chandra
  • Computer Science
  • International Joint Conference on Neural Networks…
  • 6 July 2014
TLDR
This paper presents a competitive two-island cooperative coevolution method for training recurrent neural networks on chaotic time series problems. Expand
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On the issue of separability for problem decomposition in cooperative neuro-evolution
TLDR
We show that the neural network training problem is partially separable and that the level of interdependencies changes during the learning process. Expand
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Evaluation of co-evolutionary neural network architectures for time series prediction with mobile application in finance
TLDR
The results, in general, show that recurrent neural networks have better generalisation ability when compared to feedforward networks for real-world time series problems. Expand
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Evolutionary Multi-task Learning for Modular Training of Feedforward Neural Networks
TLDR
We present a multi-task learning for neural networks that evolves modular network topologies. Expand
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Co-evolutionary multi-task learning for dynamic time series prediction
TLDR
We propose a co-evolutionary multi-task learning method for dynamic time series prediction. Expand
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Crossover-based local search in cooperative co-evolutionary feedforward neural networks
TLDR
This paper presents a new cooperative coevolution framework that incorporates crossover-based local search without adding to the computational cost. Expand
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An Encoding Scheme for Cooperative Coevolutionary Feedforward Neural Networks
TLDR
The cooperative coevolution paradigm decomposes a large problem into a set of subcomponents and solves them independently in order to collectively solve the large problem. Expand
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Encoding subcomponents in cooperative co-evolutionary recurrent neural networks
TLDR
This paper introduces a novel encoding scheme in cooperative coevolution for training recurrent neural networks. Expand
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