Statistical methods and statistical decisions making were used to arrange and analyze the primary data to get norms which are used with Geographic Information Systems (GIS) and spatial analysis programs to identify the animals production and poultry units in strategic nutrition channels, also the priorities of food insecurity through the local production and import when there is no capacity for production. The poultry production is one of the most important commodities that satisfy human body protein requirements, also the most important criteria to measure the development and prosperity of nations. The poultry fields of Babylon Governorate are located in Abi Ghareg and Al_Kifil centers according to many criteria or factors such as the population, production ratio, rivers, distance between fields and streets, and the field's spaces which identify by using TOPSIS method and GIS.
Gumbel distribution was dealt with great care by researchers and statisticians. There are traditional methods to estimate two parameters of Gumbel distribution known as Maximum Likelihood, the Method of Moments and recently the method of re-sampling called (Jackknife). However, these methods suffer from some mathematical difficulties in solving them analytically. Accordingly, there are other non-traditional methods, like the principle of the nearest neighbors, used in computer science especially, artificial intelligence algorithms, including the genetic algorithm, the artificial neural network algorithm, and others that may to be classified as meta-heuristic methods. Moreover, this principle of nearest neighbors has useful statistical featu
... Show MoreIn this paper, we introduce and discuss an algorithm for the numerical solution of two- dimensional fractional partial differential equation with parameter. The algorithm for the numerical solution of this equation is based on implicit and an explicit difference method. Finally, numerical example is provided to illustrate that the numerical method for solving this equation is an effective solution method.
The main purpose of this work is to introduce some types of fuzzy convergence sequences of operators defined on a standard fuzzy normed space (SFN-spaces) and investigate some properties and relationships between these concepts. Firstly, the definition of weak fuzzy convergence sequence in terms of fuzzy bounded linear functional is given. Then the notions of weakly and strongly fuzzy convergence sequences of operators are introduced and essential theorems related to these concepts are proved. In particular, if ( ) is a strongly fuzzy convergent sequence with a limit where linear operator from complete standard fuzzy normed space into a standard fuzzy normed space then belongs to the set of all fuzzy bounded linear operators
In this paper an estimator of reliability function for the pareto dist. Of the first kind has been derived and then a simulation approach by Monte-Calro method was made to compare the Bayers estimator of reliability function and the maximum likelihood estimator for this function. It has been found that the Bayes. estimator was better than maximum likelihood estimator for all sample sizes using Integral mean square error(IMSE).
In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.
This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc
... Show MoreThe logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .
The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result. &nbs
... Show MoreThere has been a growing interest in the use of chaotic techniques for enabling secure communication in recent years. This need has been motivated by the emergence of a number of wireless services which require the channel to provide very low bit error rates (BER) along with information security. As more and more information is transacted over wireless media, there has been increasing criminal activity directed against such systems. This paper investigates the feasibility of using chaotic communications over Multiple-Input-Multiple-Output (MIMO) channels. We have studied the performance of differential chaos shift keying (DCSK) with 2×2 Alamouti scheme and 2×1 Alamouti scheme for different chaotic maps over additive white Gaussian noise (
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