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One of the problems of optimization of concrete is to formulate a mathematical equation that shows the relationship between the various constituents of concrete and its properties. In this work, modelling of the compressive strength of concrete admixed with metakaolin was carried out using the Gene Expression Programming (GEP) algorithm. The dataset from laboratory experimentation was used for the analysis. The mixture proportions were made of three different water/binder ratios (0.4, 0.5, and 0.6), and the grades of concrete produced were grade M15 and M20. The compressive strength of the concrete was determined after 28 days of curing. The parameters used in the GEP algorithm are the input variables which include cement content, water, metakaolin content, and fine and coarse aggregate, while the response was designated as the compressive strength. The model was trained and tested using the parameters. The R-square value from the GEP algorithm was compared with the use of conventional stepwise regression analysis. With a coefficient of determination (R-square value) of 0.95, the GEP algorithm has shown to be a good alternative for modelling concrete compressive strength.

Mathematical model of compression creep for Terminalia ivorensis (Black Afara) timber were developed and presented in this paper. One-year creep test was performed in this process on Terminalia ivorensis timber samples. The creep data were fitted to linear, exponential and logarithmic regression models. The coefficients of determination for each of the model was determined. The coefficients of determination of the linear, exponential and logarithmic models were determined as 0.689, 0.650 and 0.941 respectively. Since the logarithmic model has the highest correlation with coefficient of determination of 0.941, it gave the best compression creep prediction model for the Terminalia ivorensis timber.

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