Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. One of the main advantages of using these techniques is that they require no knowledge or gradient information about the response surface. The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. One such class of these algorithms is compact Genetic Algorithm (cGA), it dramatically reduces the number of bits reqyuired to store the poulation and has a faster convergence speed. In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). Simulation results

In this paper, the effect of changes in bank deposits on the money supply in Iraq was studied by estimating the error correction model (ECM) for monthly time series data for the period (2010-2015) . The Philips Perron was used to test the stationarity and also we used Engle and Granger to test the cointegration . we used cubic spline and local polynomial estimator to estimate regression function .The result show that local polynomial was better than cubic spline with the first level of cointegration.

In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

In the analysis of multiple linear regression, the problem of multicollinearity and auto-correlation drew the attention of many researchers, and given the appearance of these two problems together and their bad effect on the estimation, some of the researchers found new methods to address these two problems together at the same time. In this research a comparison for the performance of the Principal Components Two Parameter estimator (PCTP) and The (r-k) class estimator and the r-(k,d) class estimator by conducting a simulation study and through the results and under the mean square error (MSE) criterion to find the best way to address the two problems together. The results showed that the r-(k,d) class estimator is the best esti

The environmental surfaces hygiene of college premises like classrooms play role in spreading different pathogenic bacteria, furthermore a Medical students are often potential vectors for resistant bacteria to their entourage. This study aimed to assess bacterial contamination and their susceptibility to various antimicrobial agents in the educational classroom of Al-Kindy College of medicine in two classrooms: one occupied by clinical visitor and non-clinical visitor students to evaluate and determine its health risk. In this cross-sectional study, different sites of the educational classroom of Al-Kindy College of medicine were studied.  Ninety-sex Different swab samples were collected from 8 different sites of college across bot

Image recognition is one of the most important applications of information processing, in this paper; a comparison between 3-level techniques based image recognition has been achieved, using discrete wavelet (DWT) and stationary wavelet transforms (SWT), stationary-stationary-stationary (sss), stationary-stationary-wavelet (ssw), stationary-wavelet-stationary (sws), stationary-wavelet-wavelet (sww), wavelet-stationary- stationary (wss), wavelet-stationary-wavelet (wsw), wavelet-wavelet-stationary (wws) and wavelet-wavelet-wavelet (www). A comparison between these techniques has been implemented. according to the peak signal to noise ratio (PSNR), root mean square error (RMSE), compression ratio (CR) and the coding noise e (n) of each third

Linear motor offers several features in many applications that require linear motion. Nevertheless, the presence of cogging force can deteriorate the thrust of a permanent magnet linear motor. Using several methodologies, a design of synchronous single sided linear iron-core motor was proposed. According to exact formulas with surface-mounted magnets and concentrated winding specification, which are relying on geometrical parameters. Two-dimensional performance analysis of the designed model and its multi-objective optimization were accomplished as a method to reduce the motor cogging force using MAXWELL ANSYS. The optimum model design results showed that the maximum force ripple was approximatrly reduced by 81.24%compared to the origina

In this research, some robust non-parametric methods were used to estimate the semi-parametric regression model, and then  these methods were compared using the MSE comparison criterion, different sample sizes, levels of variance, pollution rates, and three different models were used. These methods are S-LLS S-Estimation -local smoothing, (M-LLS)M- Estimation -local smoothing, (S-NW) S-Estimation-NadaryaWatson Smoothing, and (M-NW) M-Estimation-Nadarya-Watson Smoothing.

The results in the first model proved that the (S-LLS) method was the best in the case of large sample sizes, and small sample sizes showed that the

In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.