Prediction of Durability, Resilient Modulus and Resistance Value of Cement Kiln Dust-Stabilized Expansive Clay for Flexible Pavement Application Using Artificial Neural Networks

2021 ◽  
pp. 675-687
Author(s):  
Anigilaje B. Salahudeen ◽  
Mehdi Jalili ◽  
Danial R. Eidgahee ◽  
Kennedy C. Onyelowe ◽  
Mohsen K. Kabiri
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Resilient Modulus ◽  
Flexible Pavement ◽  
Cement Kiln Dust ◽  
Cement Kiln ◽  
Expansive Clay ◽  
Artificial Neural ◽  
Kiln Dust ◽  
Resistance Value

Attempt at Resilient Modulus Modeling Using Artificial Neural Networks

1996 ◽  
Vol 1540 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Erol Tutumluer ◽  
Roger W. Meier
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Network Performance ◽  
Resilient Modulus ◽  
Quality Of Data ◽  
Unsuccessful Attempt ◽  
Independent Test ◽  
Artificial Neural

The pitfalls inherent in the indiscriminate application of artificial neural networks to numerical modeling problems are illustrated. An example is used of an apparently successful (but ultimately unsuccessful) attempt at training a neural network constitutive model for computing the resilient modulus of gravels as a function of stress state and various material properties. Issues such as the quantity and quality of data needed to successfully train a neural network are explored, and the importance of an independent test set to verify network performance is examined.

Resilient Modulus and Microstructure of Cement-Kiln-Dust Stabilized Base/Subbase Aggregate

1999 ◽  
Vol 39 (6) ◽  
pp. 33-42 ◽  
Author(s):  
Jian-Hua Zhu ◽  
M. Zaman ◽  
J.G. Laguros
Keyword(s):  
Resilient Modulus ◽  
Cement Kiln Dust ◽  
Cement Kiln ◽  
Kiln Dust
Sign in / Sign up

Export Citation Format

Share Document