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Prediction of Concrete Compressive Strength by Evolutionary Artificial Neural Networks
Joint Authors
Nikoo, Mehdi
Torabian Moghadam, Farshid
Sadowski, Łukasz
Source
Advances in Materials Science and Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-03
Country of Publication
Egypt
No. of Pages
8
Abstract EN
Compressive strength of concrete has been predicted using evolutionary artificial neural networks (EANNs) as a combination of artificial neural network (ANN) and evolutionary search procedures, such as genetic algorithms (GA).
In this paper for purpose of constructing models samples of cylindrical concrete parts with different characteristics have been used with 173 experimental data patterns.
Water-cement ratio, maximum sand size, amount of gravel, cement, 3/4 sand, 3/8 sand, and coefficient of soft sand parameters were considered as inputs; and using the ANN models, the compressive strength of concrete is calculated.
Moreover, using GA, the number of layers and nodes and weights are optimized in ANN models.
In order to evaluate the accuracy of the model, the optimized ANN model is compared with the multiple linear regression (MLR) model.
The results of simulation verify that the recommended ANN model enjoys more flexibility, capability, and accuracy in predicting the compressive strength of concrete.
American Psychological Association (APA)
Nikoo, Mehdi& Torabian Moghadam, Farshid& Sadowski, Łukasz. 2015. Prediction of Concrete Compressive Strength by Evolutionary Artificial Neural Networks. Advances in Materials Science and Engineering،Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1053685
Modern Language Association (MLA)
Nikoo, Mehdi…[et al.]. Prediction of Concrete Compressive Strength by Evolutionary Artificial Neural Networks. Advances in Materials Science and Engineering No. 2015 (2015), pp.1-8.
https://search.emarefa.net/detail/BIM-1053685
American Medical Association (AMA)
Nikoo, Mehdi& Torabian Moghadam, Farshid& Sadowski, Łukasz. Prediction of Concrete Compressive Strength by Evolutionary Artificial Neural Networks. Advances in Materials Science and Engineering. 2015. Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1053685
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1053685