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Design Of Normal Concrete Mixes Using Neural Network Model

Mohd Dzulkonnain, Abu Bakar (2000) Design Of Normal Concrete Mixes Using Neural Network Model. Masters thesis, Universiti Utara Malaysia.

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Abstract

The most important factor in determining the quality of concrete is its strength. In order to achieve the required strength, a right proportion of materials in concrete such as water, cement, sand and course aggregate, need to be identified. The present mix design methods such as AC1 and DoE methods, which involve numerous calculations, design charts and table look-up are seem to be tedious and lengthy. The purpose of this project is to develop a simpler and generalized concrete mix design method using neural network techniques. A procedure for developing work models using back propagation networks is presented, and a number of issues related to data preparation are described to facilitate the development of efficient application. The findings of this project show that the application of neural network is capable of providing solutions to the civil engineering problem, particularly in designing the concrete mixes.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Concrete Mix Design, Neural Network
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty and School System > Sekolah Siswazah
Depositing User: Mrs Hafiza Mohd Akhir
Date Deposited: 24 Aug 2009 04:06
Last Modified: 24 Jul 2013 12:05
URI: http://etd.uum.edu.my/id/eprint/170

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