An algorithm for the identification of a multi-input single-output (MISO) Box-Jenkins model is developed. The method consists of several simple steps: first a high order ARX model is estimated; then the process model is calculated using the so-called Steiglitz-McBride iteration on the filtered inputoutput data; and finally the disturbance model is calculated by estimating an ARMA model of the o...

In this paper, we propose a new adaptation of the D-iteration algorithm to numerically solve the differential equations. This problem can be reinterpreted in 2D or 3D (or higher dimensions) as a limit of a diffusion process where the boundary or initial conditions are replaced by fluid catalysts. Precomputing the diffusion process for an elementary catalyst case as a fundamental block of a clas...

II complexity of the algorithm is greatly reduced especially to large scale problems. Applying this application of FSO on large number of instances and comparing with GA, the experiments results shows that these designs could improve the effectiveness, convergence rate and stability for FSO. Since various optimization algorithms take the different speed of operation or evolutionary (iteration) ...

The problem of this research tackles the process of fitting two concentric spheres to data, which arises in computational metrology. There are also many fitting criteria that could be used effectively, and the most widely used one in metrology, for example, is that of the sum of squared minimal distance. However, a simple and robust algorithm assigned for using the orthogonal distance regressio...

A method from a class of bundle methods is proposed to solve an unconstrained optimization problem. In this method an epigraph of the objective function is approximated by the set which is formed on the basis of the convex quadratic function. This method is characterized in that iteration points are constructed in terms of information obtained in the previous steps of the minimization process. ...