This study includes Estimating scale parameter, location parameter  and reliability function  for Extreme Value (EXV) distribution by two methods, namely: -
- Maximum Likelihood Method (MLE).
- Probability Weighted Moments Method (PWM).

 Used simulations to generate the required samples to estimate the parameters and reliability function of different sizes(n=10,25,50,100) , and give real values for the parameters are and , replicate the simulation experiments (R_P=1000)

This work presents a simple method for determination of the neutron reflection coefficient (n) as a function of different neutron reflector materials.A laboratory neutron source (Am-Be) with activity of 16 ci is employed with a (BF3) neutron detector. Am-BeThree types of reflector materials are used as samples, the thickness of each sample is (5cm).It is found that( ?7) is: -For polyethlyene = 0.818

The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

The distribution of the expanded exponentiated power function EEPF with four parameters, was presented by the exponentiated expanded method using the expanded distribution of the power function, This method is characterized by obtaining a new distribution belonging to the exponential family, as we obtained the survival rate and failure rate function for this distribution, Some mathematical properties were found, then we used the developed least squares method to estimate the parameters using the genetic algorithm, and a Monte Carlo simulation study was conducted to evaluate the performance of estimations of possibility using the Genetic algorithm GA.

This study employs wavelet transforms to address the issue of boundary effects. Additionally, it utilizes probit transform techniques, which are based on probit functions, to estimate the copula density function. This estimation is dependent on the empirical distribution function of the variables. The density is estimated within a transformed domain. Recent research indicates that the early implementations of this strategy may have been more efficient. Nevertheless, in this work, we implemented two novel methodologies utilizing probit transform and wavelet transform. We then proceeded to evaluate and contrast these methodologies using three specific criteria: root mean square error (RMSE), Akaike information criterion (AIC), and log

Biodiesel define as the mono-alkyl esters of vegetable oil and animal fats is an alternative diesel fuel that is steadily gaining attention because the combustion of fossil fuels such as coal, oil and natural gas has been identify as a major cause of the increase in the concentration of carbon dioxide in the earth’s atmosphere and causing global warming.
The present work concerns with estimating the physical properties experimentally such as kinematic viscosity, density, flash point and carbon residue of biodiesel that produced by the esterification reaction of methanol and oleic acid with homogeneous catalysts H2SO4 in a lab-scale packed reactive distillation column using the best operating conditions of methanol to oleic acid 8:1,