In this study, the stress-strength model R = P(Y < X < Z)  is discussed as an important parts of reliability system by assuming that the random variables follow Invers Rayleigh Distribution. Some traditional estimation methods are used    to estimate the parameters  namely; Maximum Likelihood, Moment method, and Uniformly Minimum Variance Unbiased estimator and Shrinkage estimator using three types of shrinkage weight factors. As well as, Monte Carlo simulation are used to compare the estimation methods based on mean squared error criteria.  

Improving" Jackknife Instrumental Variable Estimation method" using A class of immun algorithm with practical application

The Weibull distribution is considered one of the Type-I Generalized Extreme Value (GEV) distribution, and it plays a crucial role in modeling extreme events in various fields, such as hydrology, finance, and environmental sciences. Bayesian methods play a strong, decisive role in estimating the parameters of the GEV distribution due to their ability to incorporate prior knowledge and handle small sample sizes effectively. In this research, we compare several shrinkage Bayesian estimation methods based on the squared error and the linear exponential loss functions. They were adopted and compared by the Monte Carlo simulation method. The performance of these methods is assessed based on their accuracy and computational efficiency in estimati

New metal complexes of the ligand 4-[5-(2-hydoxy-phenyl)-[1,3,4- oxadiazol -2-ylimino methyl]-1,5-dimethyl-2-phenyl-1,2-dihydro-pyrazol-3-one (L) with the metal ions Co(II), Ni(II), Cu(II) and Zn(II) were prepared in alcoholic medium. The Schiff base was synthesized through condensate of [4-antipyrincarboxaldehyde] with[2-amino-5-(2-hydroxy-phenyl-1,3,4- oxadiazol] in alcoholic medium . Two tetradentate Schiff base ligand were used for complexation upon two metal ions of Co2+, Ni2+, Cu2+ and Zn2+ as dineucler formula M2L2.4H2O. The metal complexes were characterized by FTIR Spectroscopy, electronic Spectroscopy, elemental analysis, magnetic susceptidbility measurements, and also the ligand was characterized by 1H-NMR spectra, and m

The contribution rate of tax revenues in the federal budget is very small compared to the rate of contribution of oil revenues and this leads to negative repercussions on the Iraqi economy and the budget becomes a prisoner of high and low oil prices, and this is a problem that needs to be studied to know the extent of the impact of economic and political decisions on the size of tax revenue and The research goal is determined in studying the effect of amending the Unified Law No (26) of 2019 on the size of annual tax revenues .                                   &

Shear wave velocity is an important feature in the seismic exploration that could be utilized in reservoir development strategy and characterization. Its vital applications in petrophysics, seismic, and geomechanics to predict rock elastic and inelastic properties are essential elements of good stability and fracturing orientation, identification of matrix mineral and gas-bearing formations. However, the shear wave velocity that is usually obtained from core analysis which is an expensive and time-consuming process and dipole sonic imager tool is not commonly available in all wells. In this study, a statistical method is presented to predict shear wave velocity from wireline log data. The model concentrated to predict shear wave velocity fr

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin