A new Differential Evolution (ARDE) algorithm is introduced that automatically adapt a repository of DE strategies and parameters adaptation schemes of the mutation factor and the crossover rate to avoid the problems of stagnation and make DE responds to a wide range of function characteristics at different stages of the evolution. ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. Then a new adaptive procedure called adaptive repository (AR) has been developed to select the appropriate combinations of the JADE strategies and the parameter control schemes of the MDE_pBX to generate the next population based on their fitness values. Experimental results have been presented to confirm the reliability of the proposed ARDE over several existing adaptive DE variants. This comparison has been conducted in terms of the solution precision over twenty-one standard benchmark functions including CEC 2005 functions.
in this paper fourth order kutta method has been used to find the numerical solution for different types of first liner
In this paper, the author established some new integral conditions for the oscillation of all solutions of nonlinear first order neutral delay differential equations. Examples are inserted to illustrate the results.
This study includes the rebuilding of cities that war destroyed, which include some of the special policies that should be followed in order to build cities that war destroyed and which have importance in the national and humanitarian level, as well as some international experiences discussed including Warsaw, and the regional experiences, including Lebanon and concentrates on the foundation stone and evaluate it with global and regional experiences so that we can concluded with an integrated strategy that will achieve the best results in doing the reality that we live in these cities which are suffering from such disasters . In order to achieve the best goals we should review the best concepts and theories related to reconstruction afte
... Show MoreThe 3-parameter Weibull distribution is used as a model for failure since this distribution is proper when the failure rate somewhat high in starting operation and these rates will be decreased with increasing time .
In practical side a comparison was made between (Shrinkage and Maximum likelihood) Estimators for parameter and reliability function using simulation , we conclude that the Shrinkage estimators for parameters are better than maximum likelihood estimators but the maximum likelihood estimator for reliability function is the better using statistical measures (MAPE)and (MSE) and for different sample sizes.
Note:- ns : small sample ; nm=median sample
... Show MoreFilms of silver oxide of different thickness have been prepared by the chemical spray paralysis. Transmission and absorption spectra have recorded in order to study the effect of increasing thickness on some optical parameter such as reflectance, refractive index , and dielectric constant in its two parts . This study reveals that all these paramters affect by increasing the thickness .
Long memory analysis is one of the most active areas in econometrics and time series where various methods have been introduced to identify and estimate the long memory parameter in partially integrated time series. One of the most common models used to represent time series that have a long memory is the ARFIMA (Auto Regressive Fractional Integration Moving Average Model) which diffs are a fractional number called the fractional parameter. To analyze and determine the ARFIMA model, the fractal parameter must be estimated. There are many methods for fractional parameter estimation. In this research, the estimation methods were divided into indirect methods, where the Hurst parameter is estimated fir
... Show MoreThis Research Tries To Investigate The Problem Of Estimating The Reliability Of Two Parameter Weibull Distribution,By Using Maximum Likelihood Method, And White Method. The Comparison Is done Through Simulation Process Depending On Three Choices Of Models (?=0.8 , ß=0.9) , (?=1.2 , ß=1.5) and (?=2.5 , ß=2). And Sample Size n=10 , 70, 150 We Use the Statistical Criterion Based On the Mean Square Error (MSE) For Comparison Amongst The Methods.