A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

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In this search, we examined the factorial experiments and the study of the significance of the main effects, the interaction of the factors and their simple effects by the F test (ANOVA) for analyze the data of the factorial experience. It is also known that the analysis of variance requires several assumptions to achieve them, Therefore, in case of violation of one of these conditions we conduct a transform to the data in order to match or achieve the conditions of analysis of variance, but it was noted that these transfers do not produce accurate results, so we resort to tests or non-parametric methods that work as a solution or alternative to the parametric tests , these method

In the present work, a program for calculating the coefficients of the Aplanatic Cassegrain Telescope (ACT) system, free from the effects of spherical and coma aberrations, were constructed. In addition, the two-mirrors of the optical system, as aspherical surfaces, were adopted. This means, that the two-equations of the mirrors are assumed to be polynomial function of five even terms only. The numerical method, least-squares curve fitting method to calculate the two-mirror coefficients system, was adopted. For choosing the values and ratios that give the best results, Rayleigh Criterion (Rayleigh Limit), for purpose of comparison and preference, was adopted.

Abstract

 This research deals will the declared production planning operation in the general company of planting oils, which have  great role in production operations management who had built mathematical model for correct non-linear programming according to discounting operation during raw materials or half-made materials purchasing operation which concentration of six main products by company but discount included just three products of raw materials, and there were six months taken from the 1^st half of 2014 as a planning period has been chosen . Simulated annealing algorithm  application on non-linear model which been more difficulty than possible solution when imposed restric

An Expression for the transition charge density is investigated
where the deformation in nuclear collective modes is taken into
consideration besides the shell model transition density. The
inelastic longitudinal C2 and C4 form factors are calculated using
this transition charge density for the Ne Mg 20 24 , , Si 28 and S 32
nuclei. In this work, the core polarization transition density is
evaluated by adopting the shape of Tassie model togther with the
derived form of the ground state two-body charge density
distributions (2BCDD's). It is noticed that the core polarization
effects which represent the collective modes are essential in
obtaining a remarkable agreement between the calculated inelastic
longi

Inelastic longitudinal electron scattering form factors have been calculated for isoscaler transition
T = 0 of the (0+ ®2+ ) and (0+ ®4+ ) transitions for the 20Ne ,24Mg and 28Si nuclei. Model
space wave function defined by the orbits 1d5 2 ,2s1 2 and 1d3 2 can not give reasonable result for
the form factor. The core-polarization effects are evaluated by adopting the shape of the Tassie-
Model, together with the calculated ground Charge Density Distribution CDD for the low mass 2s-1d
shell nuclei using the occupation number of the states where the sub-shell 2s is included with an
occupation number of protons (a ) .

The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.

This work aims to study the exploding copper wire plasma parameters by optical emission spectroscopy. The emission spectra of the copper plasma have been recorded and analyzed The plasma electron temperature (Te), was calculated by Boltzmann plot, and the electron density (ne) calculated by using Stark broadening method for different copper wire diameter (0.18, 0.24 and 0.3 mm) and current
of 75A in distilled water. The hydrogen (Hα line) 656.279 nm was used to calculate the electron density for different wire diameters by Stark broadening. It was found that the electron density ne decrease from 22.4×1016 cm-3 to 17×1016 cm-3 with increasing wire diameter from 0.18 mm to 0.3 mm while the electron temperatures increase from 0.741 to