An Artificial Neural Network Model to Predict the Thermal Properties of Concrete Using Different Neurons and Activation Functions
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...
Saved in:
Main Authors: | Sehmus Fidan, Hasan Oktay, Suleyman Polat, Sarper Ozturk |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2019-01-01
|
Series: | Advances in Materials Science and Engineering |
Online Access: | http://dx.doi.org/10.1155/2019/3831813 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Using an Artificial Neural Network to Validate and Predict the Physical Properties of Self-Compacting Concrete
by: K. Thirumalai Raja, et al.
Published: (2022-01-01) -
Applicability of Artificial Neural Networks to Predict Mechanical and Permeability Properties of Volcanic Scoria-Based Concrete
by: Aref M. al-Swaidani, et al.
Published: (2018-01-01) -
Optimization and Prediction of Mechanical and Thermal Properties of Graphene/LLDPE Nanocomposites by Using Artificial Neural Networks
by: P. Noorunnisa Khanam, et al.
Published: (2016-01-01) -
Prediction of Concrete Compressive Strength by Evolutionary Artificial Neural Networks
by: Mehdi Nikoo, et al.
Published: (2015-01-01) -
Optimization of Neurons Number in Artificial Neural Network Model for Predicting the Power Production of PV Module
by: Hussain Hamdi Khalaf, et al.
Published: (2024-03-01)