Mtarfi, N. and Rais, Z. and Taleb, M. and Elmrabet, R. and Naamane, S. and Kada, K.M. and Assouag, M. and Zarrouk, A. (2016) The chemical composition modeling of cement CPJ55. Research Journal of Pharmaceutical, Biological and Chemical Sciences, 7 (5). pp. 2005-2013.

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The growing demand of cement CPJ55 requires better quality product. In this paper, it is aimed to propose prediction approaches for the 2, 7 and 28 days compressive strength of Portland composite cement (PCC) by using soft computing techniques. Plant data were collected for 8 months for the chemical and physical properties of the cement that were used in model construction and testing. The training and testing data were separated from the complete original data set by the use of Multilinear regression (MLR) model based on the training data of the cement strength was created. Testing of the model was also done within low average error levels (2.14; 2.83 and 1.89), respectively. The three models were subjected to sensitivity analysis to predict the response of the system to different values of the factors affecting the strength. The utility of the model is in the potential ability to control processing parameters to yield the desired strength levels and in providing information regarding the most favorable experimental conditions to obtain maximum compressive strength. The results obtained from the computational tests have shown that MLR is a promising technique for the prediction of cement strength.

Item Type: Article
Uncontrolled Keywords: cement, Article; chemical composition; compressive strength; controlled study; mathematical computing; mathematical model; multiple linear regression analysis; physical chemistry; prediction; process development; sensitivity analysis; statistical model
Subjects: Biochemistry, Genetics and Molecular Biology
Divisions: SCIENTIFIC PRODUCTION > Biochemistry, Genetics and Molecular Biology
Depositing User: Administrateur Eprints Administrateur Eprints
Last Modified: 31 Jan 2020 15:44

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