فهرست مطالب امیرحسین صالحی شایگان

Growing popularity of smart devices and 5G Internet, loT technology has also developed. The increase in the number of smart objects has led to an increase in data volumes and computational loads on a large scale. For this reason, cloud computing is used as a solution for this amount of data. However, given the importance of service quality, the cloud computing solution may not be responsive to latency-sensitive requests. Allocating resources in cloudy computing also reduces the cost of latency. Dynamic programming has been used due to the large number of requests and problem constraints. The proposed method reduces the cost of latency for loT requests. In this study, the proposed system modeling and algorithms were implemented for four cases. In these cases, two proposed methods have been the contribution of this research that these proposed algorithms have seen a significant reduction in the total latency cost. But as expected, the backward algorithm had a better response than the forward algorithm.

In this paper, two points guidance law of a missile is optimized based on the particle swarm search algorithm. To do so, we need to five-degree-of-freedom equations of the missile and the proportional guidance law to track the target. Next, the parameters of the law guidance are optimized using the particle swarm algorithm. As a result, the movement path of the missile and target on the horizon and vertical plane, acceleration commands, as well as the miss distance are shown. Also, the effect of axial acceleration compensation, gravitational compensation, and updated frequency on the acceleration commands and the seeker's range are investigated on the guidance law.

Artillery weapons have an important role in low height artilleries. In the first step of these weapons, due to reach a stable and controllable projectile, aerodynamically, finding angle and the initial velocity are very essential. Until now, scientists have obtained these items by modelling based on ordinary differential equations. But, in this paper, fractional differential equations of the projectile motion, which are very efficient in artillery weapons and more compatible with nature, are introduced. Then some of its properties such as trajectory, range, flight time and maximum height are studied. In addition, an inverse projectile motion is considered, i.e., we consider a problem that we know the position of motion in a special time and then we obtain angle and the initial velocity. In this way, the shooting method is applied. This method is an efficient and applicable method for solving boundary value problems. Finally, in order to study the efficiency and accuracy of the method a numerical example is given.

In this paper, two points guidance law of a missile is optimized based on the gravitational search algorithm. For this purpose, first, a five-degree-of-freedom equations of the missile and target are modeled. The proportional guidance law is, then, simulated to track the target. In the next step, the parameters of the law guidance are optimized using the gravitational search algorithm. Finally, the movement path of the missile and target on the horizon and vertical plane, acceleration commands, as well as the miss distance are shown. Also, the effect of axial acceleration compensation, gravitational compensation, updated frequency on the acceleration commands, the seeker's range as well as the maximum rate of seeker are investigated on the guidance law.

Inverse parabolic problems are the most famous ill-posed problems‎. ‎Thus using stable inexact numerical methods for approximating these problems‎, ‎causes a large perturbation‎. ‎In this paper‎, ‎we study the problem of determining the source term of the inverse source problem‎ [{partial _t}T(x,t) = kappa ,{nabla ^2}T(x,t) + g(t)delta (x - {x^*}),x in {( circ ,,1)^d},t in ( circ ,,{t_f}),] ‎from the measured data given in the form of‎ [T({x_{measure}},{t_i}) = {y_i}, ,i = 1,2, ldots ,I,] ‎(additional condition) where d = 1,2 ‎and [delta ] is the Dirac delta function and (T,g) are the unknown functions‎. ‎Then‎, ‎using the statistical spline model and applying Levenberg-Marquardt method‎, ‎we obtain an approximate solution for quasi solution g=g(t)‎‎. ‎Finally‎, ‎to show the priority and accuracy of the introduced method some numerical examples are given‎