This article aims to estimate the partially linear model by using two methods, which are the Wavelet and Kernel Smoothers. Simulation experiments are used to study the small sample behavior depending on different functions, sample sizes, and variances. Results explained that the wavelet smoother is the best depending on the mean average squares error criterion for all cases that used.

Algorithms using the second order of B -splines [B (x)] and the third order of B -splines [B,3(x)] are derived to solve 1' , 2nd and 3rd linear Fredholm integro-differential equations (F1DEs). These new procedures have all the useful properties of B -spline function and can be used comparatively greater computational ease and efficiency.The results of these algorithms are compared with the cubic spline function.Two numerical examples are given for conciliated the results of this method.

In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade

In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl

Rutting in asphalt mixtures is a very common type of distress. It occurs due to the heavy load applied and slow movement of traffic. Rutting needs to be predicted to avoid major deformation to the pavement. A simple linear viscous method is used in this paper to predict the rutting in asphalt mixtures by using a multi-layer linear computer programme (BISAR). The material properties were derived from the Repeated Load Axial Test (RLAT) and represented by a strain-dependent axial viscosity. The axial viscosity was used in an incremental multi-layer linear viscous analysis to calculate the deformation rate during each increment, and therefore the overall development of rutting. The method has been applied for six mixtures and at different tem

The scarcity of irrigation water requires procedures of specific. One of these procedures is the implementation of the rationing system (a period of the irrigation followed by a period of the dry). This system can have an impact on the properties of irrigation channels. Therefore, the study of rationing system for irrigation channels is important in both water resources and civil engineering, especially if they are constructed with gypseous soil. In order to assess the rationing system on gypseous canals stabilized with a specific ratio of cement, practical experiments were conducted to detect the effect of wetting and drying cycles on the physical and hydraulic behavior of this soil and calculation of some properties of soil such a

Soil stabilization with liquid asphalt is considered as a sustainable step towards roadway construction on problematic subgrade soil, there are no requirements to import good quality materials or to implement energy consumption, but to mix the readily available soil with liquid asphalt through the cold mix technique. In this work, collapsible soil obtained from Nasiriya was mixed with asphalt emulsion, lime, and combinations of lime and asphalt emulsion (combined stabilization) and tested in the laboratory for California bearing ratio in dry and soaked conditions. Field trial sections have been prepared with the same combinations and subjected to plate bearing test. The influence of combined stabilization on the structural properties in ter