An Accurate PSO-GA Based Neural Network to Model Growth of Carbon Nanotubes
By combining particle swarm optimization (PSO) and genetic algorithms (GA) this paper offers an innovative algorithm to train artificial neural networks (ANNs) for the purpose of calculating the experimental growth parameters of CNTs. The paper explores experimentally obtaining data to train ANNs, a...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2017-01-01
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| Series: | Journal of Nanomaterials |
| Online Access: | http://dx.doi.org/10.1155/2017/9702384 |