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Components Of Concrete Mix Designer

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2.1 INTRODUCTION
The primary objective of every concrete mix designer is to achieve the desired hardened properties of concrete in the most economical way. This aim can be fulfilled if the various concrete ingredients are relatively proportioned to yield an optimized result. In order to comply with ACI recommendations, strength tests are usually performed between 7 and 28 days after the concrete has been placed. This is time consuming and also experimental errors are inevitable because the right amount of mix needed to achieve the desired result is an iterative process. This is due to the non-linear relationship between concrete and its mix ingredients
(C. Deepa et al. 2001). In order to reduce the level of difficulty in estimating the strength of concrete by the traditional method, researchers have proposed different data-mining tools for a rapid and reliable prediction.
This section discusses the current models which have been developed to predict the compressive strength of concrete at the 28th day. Under this section, only six different models have been reviewed.
2.2 Artificial Neural Network
An artificial neural network (ANN), which is often called a neural network, is a mathematical model inspired by biological neural networks. A neural network is made up of an interconnected group of artificial neurons, and it processes information using a connectionist approach to computation. In most instances, a
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neural network is an adaptive system that changes its structure

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