๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Application of neural networks for estimation of concrete strength

โœ Scribed by Jong In Kim; Doo Kie Kim

Publisher
Korean Society of Civil Engineers
Year
2002
Tongue
English
Weight
914 KB
Volume
6
Category
Article
ISSN
1226-7988

No coin nor oath required. For personal study only.

๐Ÿ“œ SIMILAR VOLUMES

Neural networks for predicting compressi
Neural networks for predicting compressive strength of structural light weight concrete
โœ Marai M. Alshihri; Ahmed M. Azmy; Mousa S. El-Bisy ๐Ÿ“‚ Article ๐Ÿ“… 2009 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 244 KB

Neural networks procedures provide a reliant analysis in several science and technology fields. Neural network is often applied to develop statistical models for intrinsically non-linear systems because neural networks behave the advantages of simulating complex behavior of many problems. In this in

Application of a Modular Feedforward Neu
Application of a Modular Feedforward Neural Network for Grade Estimation
โœ Pejman Tahmasebi; Ardeshir Hezarkhani ๐Ÿ“‚ Article ๐Ÿ“… 2011 ๐Ÿ› Springer US ๐ŸŒ English โš– 312 KB

This article presents new neural network (NN) architecture to improve its ability for grade estimation. The main aim of this study is to use a specific NN which has a simpler architecture and consequently achieve a better solution. Most of the commonly used NNs have a fully established connection am

Neural network based approach for determ
Neural network based approach for determining the shear strength of circular reinforced concrete columns
โœ Naci Caglar ๐Ÿ“‚ Article ๐Ÿ“… 2009 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 748 KB

The objective of this study is to investigate the adequacy of neural networks (NN) as a quicker, more secure and more robust method to determine the shear strength of circular reinforced concrete columns. In the application of the NN model, a multilayer perceptron (MLP) with a back-propagation (BP)