In this paper, the Reliability Analysis with utilizing a Monte Carlo simulation (MCS) process was conducted on the equation of the collapse potential predicted by ANN to study its reliability when utilized in a situation of soil that has uncertainty in its properties. The prediction equation utilized in this study was developed previously by the authors. The probabilities of failure were then plotted against a range of uncertainties expressed in terms of coefficient of variation. As a result of reliability analysis, it was found that the collapse potential equation showed a high degree of reliability in case of uncertainty in gypseous sandy soil properties within the specified coefficient of variation (COV) for each property. When the COV ranges (0-100) for each soil properties under study, it was found also that the collapse potential equation is very well in predicting the collapse potential of gypseous sandy soils for all values of the COV lies between (0-100) % for initial water content and degree of saturation, and for values of the COV not exceed 11%, 19% for the initial dry unit weight and specific gravity respectively, as well as for the values of the COV not exceed 80%, 97% for the initial voids ratio and gypsum content respectively.
The aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.
The present paper concerns with the problem of estimating the reliability system in the stress – strength model under the consideration non identical and independent of stress and strength and follows Lomax Distribution. Various shrinkage estimation methods were employed in this context depend on Maximum likelihood, Moment Method and shrinkage weight factors based on Monte Carlo Simulation. Comparisons among the suggested estimation methods have been made using the mean absolute percentage error criteria depend on MATLAB program.
Bearing capacity of a concrete pile in fine grained cohesive soils is affected by the degree of saturation of the surrounding soil through the contribution of the matric suction. In addition, the embedded depth and the roughness of the concrete pile surface (expressed as British Pendulum Number BPN) also have their contribution to the shear strength of the concrete pile, consequently its bearing capacity. Herein, relationships among degree of saturation, pile depth, and surface roughness, were proposed as a mathematical model expressed as an equation where the shear strength of a pile can be predicted in terms of degree of saturation, depth, and BPN. Rel
... Show MoreThe problem of reconstruction of a timewise dependent coefficient and free boundary at once in a nonlocal diffusion equation under Stefan and heat Flux as nonlocal overdetermination conditions have been considered. A Crank–Nicolson finite difference method (FDM) combined with the trapezoidal rule quadrature is used for the direct problem. While the inverse problem is reformulated as a nonlinear regularized least-square optimization problem with simple bound and solved efficiently by MATLAB subroutine lsqnonlin from the optimization toolbox. Since the problem under investigation is generally ill-posed, a small error in the input data leads to a huge error in the output, then Tikhonov’s regularization technique is app
... Show MoreIn this study, dependence of gamma-ray absorption coefficient on the size of Pb particle size ranging from 200µm up to 2.5mm, using different weights of each particle size. The results show that gamma-ray attenuation coefficient is inversely proportional with the size of Pb particle size due to the reduction of the spaces between the lead particles.
Using orbit- motion limited theory, as the exact theory in calculating the ion and electron current in dusty plasma, the variations of charge number on a dust grain in Ar-plasma are studied by changing various charging parameters. Most of dependences of charge number on plasma parameters in this paper take into account the close packed effect.