Information Collection Strategies In Memetic Cooperative Neuroevolution For Time Series Prediction

Memetic algorithms have been a promising strategy to enhance neuroevolution in the past. Cooperative coevolution has been combined as memetic cooperative neuroevolution with application to chaotic time series prediction. Although the method has shown promising performance, there are limitations in the balance between global and local search. The previous study used a specific local search strategy for intensification that affected the diversity of solutions. In this study, we address this limitation by information (meme) collection strategies that maintains and refines a pool of memes during global search. We present two strategies where one is sequential and the other is concurrent meme collection implemented at different stages of evolution. In the majority of the given problems, the proposed strategies showed improvement in prediction accuracy over the related methods.

[1]  Giovanni Iacca,et al.  Ockham's Razor in memetic computing: Three stage optimal memetic exploration , 2012, Inf. Sci..

[2]  Chi-Keong Goh,et al.  Co-evolutionary multi-task learning with predictive recurrence for multi-step chaotic time series prediction , 2017, Neurocomputing.

[3]  Kalyanmoy Deb,et al.  A Computationally Efficient Evolutionary Algorithm for Real-Parameter Optimization , 2002, Evolutionary Computation.

[4]  Francisco Herrera,et al.  Real-Coded Memetic Algorithms with Crossover Hill-Climbing , 2004, Evolutionary Computation.

[5]  L. Glass,et al.  Oscillation and chaos in physiological control systems. , 1977, Science.

[6]  Mengjie Zhang,et al.  Crossover-based local search in cooperative co-evolutionary feedforward neural networks , 2012, Appl. Soft Comput..

[7]  Mengjie Zhang,et al.  An Encoding Scheme for Cooperative Coevolutionary Feedforward Neural Networks , 2010, Australasian Conference on Artificial Intelligence.

[8]  Carlos Cotta,et al.  Memetic algorithms and memetic computing optimization: A literature review , 2012, Swarm Evol. Comput..

[9]  F. Takens.  Detecting strange attractors in turbulence , 1981 .

[10]  César Hervás-Martínez,et al.  Multi-objective cooperative coevolution of artificial neural networks (multi-objective cooperative networks) , 2002, Neural Networks.

[11]  Natalio Krasnogor,et al.  Toward truly "memetic" memetic algorithms: discussion and proof of concepts , 2002 .

[12]  Risto Miikkulainen,et al.  Accelerated Neural Evolution through Cooperatively Coevolved Synapses , 2008, J. Mach. Learn. Res..

[13]  Rohitash Chandra,et al.  Enhancing Competitive Island Cooperative Neuro-Evolution Through Backpropagation for Pattern Classification , 2015, ICONIP.

[14]  César Hervás-Martínez,et al.  COVNET: a cooperative coevolutionary model for evolving artificial neural networks , 2003, IEEE Trans. Neural Networks.

[15]  Mengjie Zhang,et al.  On the issue of separability for problem decomposition in cooperative neuro-evolution , 2012, Neurocomputing.

[16]  Yew-Soon Ong,et al.  A proposition on memes and meta-memes in computing for higher-order learning , 2009, Memetic Comput..

[17]  Yew-Soon Ong,et al.  Memetic Computation—Past, Present & Future [Research Frontier] , 2010, IEEE Computational Intelligence Magazine.

[18]  Carlos A. Coello Coello,et al.  Use of cooperative coevolution for solving large scale multiobjective optimization problems , 2013, 2013 IEEE Congress on Evolutionary Computation.

[19]  R. Salomon.  Re-evaluating genetic algorithm performance under coordinate rotation of benchmark functions. A survey of some theoretical and practical aspects of genetic algorithms. , 1996, Bio Systems.

[20]  R. Lewontin.  ‘The Selfish Gene’ , 1977, Nature.

[21]  Kenneth A. De Jong,et al.  Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents , 2000, Evolutionary Computation.

[22]  Rohitash Chandra,et al.  Memetic Cooperative Neuro-Evolution for Chaotic Time Series Prediction , 2016, ICONIP.

[23]  X. Yao,et al.  Scaling up fast evolutionary programming with cooperative coevolution , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[24]  Mengjie Zhang,et al.  Cooperative coevolution of Elman recurrent neural networks for chaotic time series prediction , 2012, Neurocomputing.

[25]  Pierre Gançarski,et al.  Darwinian, Lamarckian, and Baldwinian (Co)Evolutionary Approaches for Feature Weighting in $K$-means-Based Algorithms , 2008, IEEE Transactions on Evolutionary Computation.

[26]  Rohitash Chandra.  Memetic cooperative coevolution of Elman recurrent neural networks , 2014, Soft Comput..