Based on the Differential Transformation Method (DTM), a solution procedure for solving a class of nonlinear quadratic optimal control problems is presented in this paper. The reason for selecting this solution procedure is the less computational cost in comparison with the ordinary solution methods of original problem. First, the problem is converted to a two-point boundary value problem then the new problem is transferred into a set of algebraic equations by applying the differential transformation properties. By presenting the algorithmic solution procedure, two numerical examples are given to demonstrate the simplicity and efficiency of the new method.

In this paper we consider the single facility location problem with respect to a given set of existing facilities in the presence of an arc-shaped barrier. A barrier is considered a region where neither facility location nor travelling is permitted. We present a mixed-integer nonlinear programming model for this single facility location problem. The objective of this problem is to locate this single facility such that the sum of the rectilinear distances from the facility to the demand points is minimized. Test problems are presented to illustrate the applicability of the proposed model.

In this article, we present a new algorithm for solving Semi-Infinite Linear Programming (SILP) problems based on an artificial neural network concept. First the local reduction method for solving the SILP problems is introduced. Based on the local reduction method, the Karush-Kuhn-Tucker (KKT) conditions and gradient method are used to convert the SILP problem to an unconstrained optimization problem; then, a neural network model is constructed to solve it. Numerical example has been employed to indicate the accuracy of the new method.

In this article we have tried to control your car and park it was good. the car park there are different methods such as using fuzzy controller, genetic algorithm, neural networks, image processing, sensors and .... use In this paper, fuzzy control method is used. Park for three types of controllers is proposed in this paper. for park in the rear and park in front of the fuzzy controller if the primary controller having a first car or the car park for the start of the second controller in the output. the second controller uses the vehicle away from the table and change the angle of rotation angle of the car makes the car move. park is also only a single controller for the vertical input, single output is used to move the vehicle entrance and exit angle of the vehicle steering angle is changed. this has the advantage over other papers that extra controller to start the car park used in most papers on this subject has been addressed.

The Shape-Measure method for solving optimal shape design problems (OSD) in cartesian coordinates is divided into two steps. First, for a fixed shape (domain), the problem is transferred to the space of positive Radon measures and relaxed to a linear programming in which its optimal coefficients determine the optimal pair of trajectory and control. Then, a standard minimizing algorithm is used to identify the best shape. Here we deal with the best standard algorithm to identify the optimal solution for an OSD sample problem governed by an elliptic boundary control problem.

In this paper, we solve nonlinear fractional differential equations by Bernstein polynomials. Firstly, we derive the Bernstein polynomials (BPs) operational matrix for the fractional derivative in the Caputo sense, which has not been undertaken before. This method reduces the problems to a system of algebraic equations. The results obtained are in good agreement with the analytical solutions and the numerical solutions in open literatures. Also, the solutions approach to classical solutions as the order of the fractional derivatives approach to 1.

Today by increasing population growth, poultry farming has found an important place , one of these solution for poultry farming is to using incubator . Today one the main methods in incubation industry that works smart , this system can be fuzzy logic. In this article we plan to study getting fuzzy of three parameter such as temperature, moisture and oxygen that they have an effective role in the incubation process in incubator. Also in this article we tries to achieve to the greatest efficiency in terms of number of born chickens which was born from eggs and have a system with precise control- finally we survey the average of regression of these three fuzzy parameter.

In this paper, an intelligent nonlinear controller is presented by intelligent tuning of the backstepping method parameters using Bees Algorithm. The proposed controller is utilized to control of chaos of Gyro system. The backstepping method consists of parameters which could have positive values. The parameters are usually chosen optional by trial and error method. The improper selection of the parameters leads to inappropriate responses or even may lead to instability of the system. The proposed optimal backstepping controller without trial and error determines the parameters of backstepping controller automatically and intelligently by minimizing the Integral of Time multiplied Absolute Error (ITAE) and squared controller output. Finally, the efficiency of the proposed intelligent backstepping controller is illustrated by implementing the method on the Gyro chaotic system.

This paper introduces a cutting-plane algorithm for solving semi-infinite linear programming problems in fuzzy case; the problem contains a crisp objective linear function and the infinite number of fuzzy linear constraints. In the first step; the designed algorithm solves a LP problem, which was created by the ranking function method based on a fuzzy sub-problem of the original one. In each iteration of the proposed algorithm, a cutting is created by adding a fuzzy constraint of the original problem to the fuzzy sub-problem. The convergence of the algorithm is proved and some numerical examples are given.

The use of financial ratios for predicting companies' bankruptcy has always been considered by universities and economical institutions especially banks and other financial organizations. In such studies, statistical models like multiple distinctive analyses (MDA), logit Analysis, probit Analysis have usually been used. In this study, the prediction of accepted productive companies' bankruptcy in Tehran negotiable papers exchange has been paid by the use of artificial neural network (ANN) model and we have also made a comprehensive review on the models of bankruptcy prediction. In this study, artificial neural network model with logistic regression (LR) statistical model that is a useful statistical model in bankruptcy prediction has been compared. Our findings from these models on the basis of 80 companies' data showed that artificial neural network model has more accuracy than logistic regression statistical model in bankruptcy prediction.

Clustering algorithms classify data points into meaningful groups based on their similarity to exploit useful information from data points. They can be divided into categories: Sequential algorithms, Hierarchical clustering algorithms, Clustering algorithms based on cost function optimization and others. In this paper, we discuss some hierarchical clustering algorithms and their attributes, and then compare them with each other.