The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Evolving artificial neural networks
Abstract
Learning and evolution are two fundamental forms of adaptation. There has been a great interest in combining learning and evolution with artificial neural networks (ANNs) in recent years. This paper: 1) reviews different combinations between ANNs and evolutionary algorithms (EAs), including using EAs to evolve ANN connection weights, architectures, learning rules, and input features; 2) discusses different search operators which have been used in various EAs; and 3) points out possible future research directions. It is shown, through a considerably large literature review, that combinations between ANNs and EAs can lead to significantly better intelligent systems than relying on ANNs or EAs alone.
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Cites
A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
No free lunch theorems for optimization
Wolpert, D. H., & Macready, W. G. (1997) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.585893 · Cited by 14,237
WIDROW, B., & HOFF, M. E. (1960) · doi:10.21236/ad0241531 · Cited by 4,009
Evolutionary computation: Comments on the history and current state
Back, T., Hammel, U., & Schwefel, H.-P. (1997) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.585888 · Cited by 1,536 · cited 1×
“Fogel [15] and B ¨ ack et al. [16] give a good introduction to various evolutionary algorithms for optimization.”
Background(2013) · doi:10.4324/9780203763247 · Cited by 400
Cited by
Neural Architecture Search: A Survey
Elsken, T., Metzen, J. H., & Hutter, F. (2018) · arXiv · doi:10.48550/arxiv.1808.05377 · Cited by 1,763
Artificial intelligence in digital pathology — new tools for diagnosis and precision oncology
Bera, K., Schalper, K. A., Rimm, D. L., Velcheti, V., & Madabhushi, A. (2019) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-019-0252-y · Cited by 1,698
An optimizing BP neural network algorithm based on genetic algorithm
Ding, S., Su, C., & Yu, J. (2011) · Artificial Intelligence Review · doi:10.1007/s10462-011-9208-z · Cited by 802
Elsken, T., Metzen, J. H., & Hutter, F. (2019) · The Springer Series on Challenges in Machine Learning · doi:10.1007/978-3-030-05318-5_3 · Cited by 785
Miikkulainen, R., Liang, J., Meyerson, E., Rawal, A., Fink, D., Francon, O., Raju, B., Shahrzad, H., Navruzyan, A., Duffy, N., et al. (2019) · Artificial Intelligence in the Age of Neural Networks and Brain Computing · doi:10.1016/b978-0-12-815480-9.00015-3 · Cited by 760
Metadata
- Authors
- Yao, X.
- Venue
- Proceedings of the IEEE
- Published
- 1999
- Volume
- 87
- Issue
- 9
- Pages
- 1423-1447
- ISSN
- 0018-9219 (ISSN-L)
- OpenAlex
- W2124290836
- Cited by
- 2,981
- References
- 5
- FWCI
- 50.46
- Type
- journal article
- Language
- en
- Open access
- closed
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