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The compressive strength is most reliable parameter to evaluate the ability of concrete in resisting compression. The paper presents a study on prediction of the compressive strength of roller compacted concrete using multiple regression analysis (MRA) and artificial neural networks (ANN). The compressive strength of roller compacted concrete was obtained experimentally at 3, 7 and 28 days of curing. The samples were prepared by varying the percentage of cement and superplasticizer. The data were organized in three different groups randomly using R statistical software. The models were executed with cement content, coarse and fine aggregate, superplasticizer content, water content and days of aging as input parameters that were used to predict compressive strength which is the output parameter. The analysis was performed using multiple regression and artificial neural networks methodology. Statistical measures like root-mean-square error (RMSE), mean absolute error (MAE) and coefficient of determination are used to assess the performance of models. The determination coefficient from multiple regression analysis is found to be 0.975 and 0.886 for testing and validating the data correspondingly, whereas the determination coefficient from artificial neural network analysis is found to be 0.9 for both testing and validating the data. The results obtained from ANN are highly accurate because of its own topology.

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Slopes are required in the construction of Highways, Railways, Earthen dams, canal banks, levees and at many other locations. The construction of embankment over the ground is not possible in a vertical way. The Soil can be piled up with slope only. The cost of earthwork is minimum if the slopes are steepest but the Steeper slopes are not safe as per stability conditions because it may fail in shear. The only force acting on the piled earth is gravity force. This gravitational force produces shear in the soil and causes slippage. The failure lead to loss of property and life. There is a lesser chance of slippage of soil if we provide more bottom width compared to its top width. But it requires more area and more earth to fill. So, it is uneconomical. In the present study, the soil was collected from the highway extension project, from the geotechnical investigation it was identified that the soil shear strength was quite low. To improve shear characteristics and to decrease the dry density of soil, it is to be stabilized with a lightweight material, possessing good frictional characteristics. A waste by-product was identified from the industry of nearest village called Manganese (Mn) slag. The soil was stabilized with various percentages of Mn slag, from the geotechnical characterization, an optimum % of slag is selected as 10 %. An embankment slope is assumed for further slope stability analysis. The analysis is carried out on two slopes, one is made with ordinary soil and the other is soil stabilized with optimum Mn slag %. Both stabilized soil embankment and ordinary soil embankment are analysed by using the Method of slices and the final results were compared.