Intended for getting good estimates with more accurate results, we must choose the appropriate method of estimation. Most of the equations in classical methods are linear equations and finding analytical solutions to such equations is very difficult. Some estimators are inefficient because of problems in solving these equations. In this paper, we will estimate the survival function of censored data by using one of the most important artificial intelligence algorithms that is called the genetic algorithm to get optimal estimates for parameters Weibull distribution with two parameters. This leads to optimal estimates of the survival function. The genetic algorithm is employed in the method of moment, the least squares method and the weighted

Due to the lack of statistical researches in studying with existing (p) of Exogenous Input variables, and there contributed in time series phenomenon as a cause, yielding (q) of Output variables as a result in time series field, to form conceptual idea similar to the Classical Linear Regression that studies the relationship between dependent variable with explanatory variables. So highlight the importance of providing such research to a full analysis of this kind of phenomena important in consumer price inflation in Iraq. Were taken several variables influence and with a direct connection to the phenomenon and analyzed after treating the problem of outliers existence in the observations by (EM) approach, and expand the sample size (n=36) to

The aim of this study is to propose reliable equations to estimate the in-situ concrete compressive strength from the non-destructive test. Three equations were proposed: the first equation considers the number of rebound hummer only, the second equation consider the ultrasonic pulse velocity only, and the third equation combines the number of rebound hummer and the ultrasonic pulse velocity. The proposed equations were derived from non-linear regression analysis and they were calibrated with the test results of 372 concrete specimens compiled from the literature. The performance of the proposed equations was tested by comparing their strength estimations with those of related existing equations from literature. Comparis

 Researchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat

It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna

Regression testing is a crucial phase in the software development lifecycle that makes sure that new changes/updates in the software system don’t introduce defects or don’t affect adversely the existing functionalities. However, as the software systems grow in complexity, the number of test cases in regression suite can become large which results into more testing time and resource consumption. In addition, the presence of redundant and faulty test cases may affect the efficiency of the regression testing process. Therefore, this paper presents a new Hybrid Framework to Exclude Similar & Faulty Test Cases in Regression Testing (ETCPM) that utilizes automated code analysis techniques and historical test execution data to

It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna

In this paper, we derived an estimator of reliability function for Laplace distribution with two parameters using Bayes method with square error loss function, Jeffery’s formula and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived Bayesian estimator compared to the maximum likelihood of this function and moment method using simulation technique by Monte Carlo method under different Laplace distribution parameters and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator and moment estimator in all samples sizes

A comparison study was made for the reaction of triruthenium carbonyl Ru3(CO)12 with azoarene ArN=NAr . This reaction was monitored in two kinds of solvents , toluene , and n- octane , which yielded new triruthenium carbonyl complex Ru3(μ3-NAr)2(CO)9 . The reactions of azoarenes ArN=NAr with Ru3(CO)12 formed the following trinuclear compound of Ru3((μ3- NAr)2(CO)9 (Ar-C6H4Br-4) in law yield . In addition , to new isomers species of mononuclear cyclometallated of Ru(BrC6H4N-NC6H4NBr-4)2(CO)2 in different percentages . The mechanism of the reaction domenstrates that the formation of trinuclear bis arylimido complexes , and ortho metallated was , the result of cleavage of nitrogen –nitrogen bond . Monitoring this gave evidence that the rea

The confirming of security and confidentiality of multimedia data is a serious challenge through the growing dependence on digital communication. This paper offers a new image cryptography based on the Chebyshev chaos polynomials map, via employing the randomness characteristic of chaos concept to improve security. The suggested method includes block shuffling, dynamic offset chaos key production, inter-layer XOR, and block 90 degree rotations to disorder the correlations intrinsic in image. The method is aimed for efficiency and scalability, accomplishing  complexity order for n-pixels over specific cipher rounds. The experiment outcomes depict great resistant to cryptanalysis attacks, containing statistical, differential and brut