Asynchronous Differential Evolution with Strategy Adaptation for Global Numerical Optimization
Author:
Affiliation:
1. Department of Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea
2. CTO Department, LG Electronics, Seoul, Republic of Korea
Funder
This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. NRF-2017R1C1B2012752).
Publisher
ACM Press
Reference13 articles.
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2. Choi, T. J., & Ahn, C. W. (2017, February). An Improved Differential Evolution Algorithm and Its Application to Large-Scale Artificial Neural Networks. In Journal of Physics: Conference Series (Vol. 806, No. 1, p. 012010). IOP Publishing.
3. Choi, T. J., & Ahn, C. W. (2017, December). Adaptive Cauchy Differential Evolution with Strategy Adaptation and Its Application to Training Large-Scale Artificial Neural Networks. In International Conference on Bio-Inspired Computing: Theories and Applications (pp. 502--510). Springer, Singapore.
4. Choi, T. J., & Ahn, C. W. (2017). Artificial life based on boids model and evolutionary chaotic neural networks for creating artworks. Swarm and Evolutionary Computation.
5. Choi, T. J., Ahn, C. W., & An, J. (2013). An adaptive cauchy differential evolution algorithm for global numerical optimization. The Scientific World Journal, 2013.
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