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Publications (2)0 Total impact

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    ABSTRACT: Concrete is the sustainable construction material, which is most widely used in the world as it provides superior fire resistance, gains strength over time and gives an extremely long service life. Its annual consumption is estimated between 21 and 31 billion tones. The paper is aimed at guiding the selection of available materials andproportioning them as to produce the most economical concrete suitable for the desired purpose. According to the National Council for Cement and Building Materials (NCBM), New Delhi, the compressive strength of concrete is governed generally, by the water-cement ratio. The mineral admixtures like fly ash, ground granulated blast furnace, silica fume and fine aggregates also influence it. The main purpose of this paper is to find the accuracy for the compressive strength of high performance concrete by using classification algorithms like Multilayer Perceptron, Rnd tree models and C-RT regression. The result from this study suggests that tree based models perform remarkably well for designing the concrete mix.
    International Journal of Engineering Science and Technology. 01/2010;
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    ABSTRACT: Concrete is the safest and sustainable construction materialwhich is most widely used in the world as it provides superiorfire resistance, gains strength over time and gives an extremelylong service life. Its annual consumption is estimated between 21and 31 billion tones. Designing a concrete mix involves theprocess of selecting suitable ingredients of concrete anddetermining their relative amounts with the objective ofproducing a concrete of the required, strength, durability, andworkability as economically as possible. According to theNational Council for Cement and Building Materials (NCBM),New Delhi, the compressive strength of concrete is governedgenerally, by the water-cement ratio. The mineral admixtureslike fly ash, ground granulated blast furnace, silica fume and fineaggregates also influence it. The main purpose of this paper is topredict the compressive strength of the high performanceconcrete by using classification algorithms like MultilayerPerceptron, M5P Tree models and Linear Regression. The resultfrom this study suggests that tree based models performremarkably well in predicting the compressive strength of theconcrete mix.
    International Journal of Computer Applications. 01/2010;