Particle swarm optimization trained neural network for structural failure prediction of multistoried RC buildings

Faulty structural design may cause multistory reinforced concrete (RC) buildings to collapse suddenly. All attempts are directed to avoid structural failure as it leads to human life danger as well as wasting time and property. Using traditional methods for predicting structural failure of the RC bu...

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Veröffentlicht in:	Neural computing & applications Jg. 28; H. 8; S. 2005 - 2016
Hauptverfasser:	Chatterjee, Sankhadeep, Sarkar, Sarbartha, Hore, Sirshendu, Dey, Nilanjan, Ashour, Amira S., Balas, Valentina E.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.08.2017 Springer Nature B.V
Schlagworte:	Accuracy Algorithms Artificial Intelligence Artificial neural networks Classifiers Collapse Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Concrete construction Data Mining and Knowledge Discovery Feature extraction Hazards Image Processing and Computer Vision Learning theory Machine learning Multistory buildings Neural networks Original Article Particle swarm optimization Predictions Probability and Statistics in Computer Science Reinforced concrete Root-mean-square errors Structural design Structural failure Multilayer perceptron feed-forward network Structural failure Cross-entropy Scaled conjugate gradient algorithm Artificial neural network Reinforced concrete structures Particle swarm optimization
ISSN:	0941-0643, 1433-3058
Online-Zugang:	Volltext
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