Journal
COATINGS
Volume 7, Issue 4, Pages -Publisher
MDPI
DOI: 10.3390/coatings7040049
Keywords
cement mortar; overlay; concrete substrate; interlayer bond; pull-off adhesion; artificial intelligence; metaheuristics; imperialist competitive algorithm; genetic algorithm; particle swarm optimization
Categories
Funding
- National Centre of Science, Poland [2014/15/D/ST8/00550]
Ask authors/readers for more resources
The article presents the hybrid metaheuristic-neural assessment of the pull-off adhesion in existing multi-layer cement composites using artificial neural networks (ANNs) and the imperialist competitive algorithm (ICA). The ICA is a metaheuristic algorithm inspired by the human political-social evolution. This method is based solely on the use of ANNs and two non-destructive testing (NDT) methods: the impact-echo method (I-E) and the impulse response method (IR). In this research, the ICA has been used to optimize the weights of the ANN. The combined ICA-ANN model has been compared to the genetic algorithm (GA) and particle swarm optimization (PSO) to evaluate its accuracy. The results showed that the ICA-ANN model outperforms other techniques when testing datasets in terms of both effectiveness and efficiency. As presented in the validation stage, it is possible to reliably map the adhesion level on a tested surface without local damage to the latter.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available