Research and Application of Improved AGP Algorithm for Structural Optimization Based on Feedforward Neural Networks
Ruliang Wang,
Huanlong Sun,
Benbo Zha and
Lei Wang
Mathematical Problems in Engineering, 2015, vol. 2015, 1-6
Abstract:
The adaptive growing and pruning algorithm (AGP) has been improved, and the network pruning is based on the sigmoidal activation value of the node and all the weights of its outgoing connections. The nodes are pruned directly, but those nodes that have internal relation are not removed. The network growing is based on the idea of variance. We directly copy those nodes with high correlation. An improved AGP algorithm (IAGP) is proposed. And it improves the network performance and efficiency. The simulation results show that, compared with the AGP algorithm, the improved method (IAGP) can quickly and accurately predict traffic capacity.
Date: 2015
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2015/481919.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2015/481919.xml (text/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:481919
DOI: 10.1155/2015/481919
Access Statistics for this article
More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().