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Investigations of failures of soil masses are subjects touching both geology and engineering. These investigations call the joint efforts of engineering geologists and geotechnical engineers. Geotechnical engineers have to pay particular attention to geology, ground water, and shear strength of soils in assessing slope stability. Artificial neural networks (ANNs) are very sophisticated modeling techniques, capable of modeling extremely complex functions. In particular, neural networks are nonlinear. In this research, with respect to the above advantages, ANN systems consisting of multilayer perceptron networks are developed to predict slope stability in a specified location, based on the available site investigation data from Noabad, Mazandaran, Iran. Several important parameters, including total stress, effective stress, angle of slope, coefficient of cohesion, internal friction angle, and horizontal coefficient of earthquake, were used as the input parameters, while the slope stability was the output parameter. The results are compared with the classical methods of limit equilibrium to check the ANN model's validity.Keywords Slope stability . Artificial neural network . Nonlinear . NoabadErosion of a slope by a river or other natural agent This erosion can take place at the toe of the slope or along a weaker layer in it. It can happen due to the effect of a tidal current in a river involving sediment transport. The process Arab J Geosci (

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Abstract:In the literature, studies show that nanosilica particles and artificial pozzolans possessing can improve structural properties of cement-based materials. This paper studies the effect of cement and nanosilica on the engineering properties (compaction, unconfined compressive strength) of sand. Three different cement ratios (5, 9, and 14% by weight of dry sand) were mixed with four different nano silica ratios (0, 5, 10, and 15% by weight of cement), and then compacted into a cylindrical specimen. The results of the study presented that the addition of the cement and nanosilica improves the engineering properties of sands. The increase of maximum dry unit weight of sand was noted with the increase in the cement content. The presence of nanosilica in optimal percentages can significantly improve the mechanical properties of cement sand.

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