An Artificial Neural Network Model to Predict the Thermal Properties of Concrete Using Different Neurons and Activation Functions
Joint Authors
Fidan, Sehmus
Oktay, Hasan
Polat, Suleyman
Ozturk, Sarper
Source
Advances in Materials Science and Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-04-01
Country of Publication
Egypt
No. of Pages
13
Abstract EN
Growing concerns on energy consumption of buildings by heating and cooling applications have led to a demand for improved insulating performances of building materials.
The establishment of thermal property for a building structure is the key performance indicator for energy efficiency, whereas high accuracy and precision tests are required for its determination which increases time and experimental costs.
The main scope of this study is to develop a model based on artificial neural network (ANN) in order to predict the thermal properties of concrete through its mechanical characteristics.
Initially, different concrete samples were prepared, and their both mechanical and thermal properties were tested in accordance with ASTM and EN standards.
Then, the Levenberg–Marquardt algorithm was used for training the neural network in the single hidden layer using 5, 10, 15, 20, and 25 neurons, respectively.
For each thermal property, various activation functions such as tangent sigmoid functions and triangular basis functions were used to examine the best solution performance.
Moreover, a cross-validation technique was used to ensure good generalization and to avoid overtraining.
ANN results showed that the best overall R2 performances for the prediction of thermal conductivity, specific heat, and thermal diffusivity were obtained as 0.996, 0.983, and 0.995 for tansig activation functions with 25, 25, and 20 neurons, respectively.
The performance results showed that there was a great consistency between the predicted and tested results, demonstrating the feasibility and practicability of the proposed ANN models for predicting the thermal property of a concrete.
American Psychological Association (APA)
Fidan, Sehmus& Oktay, Hasan& Polat, Suleyman& Ozturk, Sarper. 2019. An Artificial Neural Network Model to Predict the Thermal Properties of Concrete Using Different Neurons and Activation Functions. Advances in Materials Science and Engineering،Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1119873
Modern Language Association (MLA)
Fidan, Sehmus…[et al.]. An Artificial Neural Network Model to Predict the Thermal Properties of Concrete Using Different Neurons and Activation Functions. Advances in Materials Science and Engineering No. 2019 (2019), pp.1-13.
https://search.emarefa.net/detail/BIM-1119873
American Medical Association (AMA)
Fidan, Sehmus& Oktay, Hasan& Polat, Suleyman& Ozturk, Sarper. An Artificial Neural Network Model to Predict the Thermal Properties of Concrete Using Different Neurons and Activation Functions. Advances in Materials Science and Engineering. 2019. Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1119873
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1119873