Estimating of Compressive Strength of Concrete with Artificial Neural Network According to Concrete Mixture Ratio and Age
Journal Title: International Journal of Intelligent Systems and Applications in Engineering - Year 2016, Vol 4, Issue 3
Abstract
Compressive strength of concrete is one of the most important elements for an existing building and a new structure to be built. While obtaining the desired compressive strength of concrete with an appropriate mix and curing conditions for a new structure, with non-destructive testing methods for an existing structure or by taking core samples the concrete compressive strength are determined. One of the most important factors that affects the concrete compressive strength is age of concrete. In this study, it is attempted to estimate compressive strength, modelling Artificial Neural Networks (ANN) and using different mixture ratios and compressive strength of concrete samples at different ages. In accordance with obtained data’s in the estimation of concrete compressive strength, ANN could be used safely.
Authors and Affiliations
Ilker Ali OZKAN*| Selcuk University, Technology Faculty, Computer Engineering, Konya, Turkey, Mustafa ALTIN| Selcuk University Higher School of Vocational and Technical Sciences, Konya, Turkey
Keywords
Related Articles
- EP ID EP803
- DOI 10.18201/ijisae.263977
- Views 533
- Downloads 26
Lossless Text Compression Technique with LSB Technique to Hide Secret Message inside an Image (CLSB)
This paper presents CLSB algorithm to improve and increase the security ofhiding message inside an image by using Least Significant Bit (LSB) method. This research attempts to improve the way has been introduced in [1],...
Particle Swarm Optimization Based Approach for Location Area Planning in Cellular Networks
Location area planning problem plays an important role in cellular networks because of the trade-off caused by paging and registration signalling (i.e., location update). Compromising between the location update and the...
Dependability Assessment of the Railway Signalling Systems Based on the Stochastic Petri Nets Analysis
In this article, we propose a methodology to evaluate the performances of the railway signalling systems in terms of the availability. Firstly, level crossings in Morocco are presented. Secondly, a railway signalling sys...
The Classification of Eye State by Using kNN and MLP Classification Models According to the EEG Signals
What is widely used for classification of eye state to detect human’s cognition state is electroencephalography (EEG). In this study, the usage of EEG signals for online eye state detection method was proposed. In this s...
Intrusion Detection Forecasting Using Time Series for Improving Cyber Defence
The strength of time series modeling is generally not used in almost all current intrusion detection and prevention systems. By having time series models, system administrators will be able to better plan resource alloca...