In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl
... Show MoreAlgorithms using the second order of B -splines [B (x)] and the third order of B -splines [B,3(x)] are derived to solve 1' , 2nd and 3rd linear Fredholm integro-differential equations (F1DEs). These new procedures have all the useful properties of B -spline function and can be used comparatively greater computational ease and efficiency.The results of these algorithms are compared with the cubic spline function.Two numerical examples are given for conciliated the results of this method.
Linear programming currently occupies a prominent position in various fields and has wide applications, as its importance lies in being a means of studying the behavior of a large number of systems as well. It is also the simplest and easiest type of models that can be created to address industrial, commercial, military and other dilemmas. Through which to obtain the optimal quantitative value. In this research, we dealt with the post optimality solution, or what is known as sensitivity analysis, using the principle of shadow prices. The scientific solution to any problem is not a complete solution once the optimal solution is reached. Any change in the values of the model constants or what is known as the inputs of the model that will chan
... Show MoreIn this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade
... Show MoreThe importance of this research in studying the actor life existence on the stage through the performance art;where as all the literary theatrical dimensions didn't ignore the importance of the actor's performance.
So, it is shed a light on the nature of the scenery in the actor's performance and what its representations in the temporary directions ……..
The research set off from the imitation as a human instinct to the performance of the actor in post-modernity theater; so the researcher found that there is a question must be answered which is :Is the actor live a regression state in his theatrical performance ,or that the performance of the actor connect with collective conscience of human being which is repeated in certain
Abstract
The research aims to study the role of e-government in enhancing institutional performance. The dimensions of e-government are: (support and commitment of senior management, technical structures, organization and human resources, knowledge and information, work procedures, attention to citizens' satisfaction, and client parties),while the dimensions of institutional performance are: (Service improvement, innovation, efficiency and effectiveness).
The research used electronic questionnaire as a main tool for data collection, The questionnaire included all the employees in the e-government project in Department of Government Coordinate and Citizen Affairs at the General Secretariat of the C
... Show MoreAverage per capita GDP income is an important economic indicator. Economists use this term to determine the amount of progress or decline in the country's economy. It is also used to determine the order of countries and compare them with each other. Average per capita GDP income was first studied using the Time Series (Box Jenkins method), and the second is linear and non-linear regression; these methods are the most important and most commonly used statistical methods for forecasting because they are flexible and accurate in practice. The comparison is made to determine the best method between the two methods mentioned above using specific statistical criteria. The research found that the best approach is to build a model for predi
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