Tuning Genetic Algorithm Parameters to Improve Convergence Time
نویسندگان
چکیده
منابع مشابه
Controller Parameters Tuning Using Genetic Algorithm and Neural Model
The paper deals with a controller design for the nonlinear processes using genetic algorithm and neural model. The aim was to improve the control performance using genetic algorithm for optimal PID controller tuning. The plant model has been identified via an artificial neural network from measured data. The genetic algorithm represents an optimisation procedure, where the cost function to be m...
متن کاملA design algorithm using external perturbation to improve Iterative Feedback Tuning convergence
Iterative Feedback Tuning constitutes an attractive control loop tuning method for processes in the absence of sufficient process insight. It is a purely data driven approach to optimization of the loop performance. The standard formulation ensures an unbiased estimate of the loop performance cost function gradient, which is used in a search algorithm for minimizing the performance cost. A slow...
متن کاملThe parameters tuning for evolutionary synthesis algorithm
This paper covers the evaluation and fine-tuning of different values of genetic operator’s parameters in the process of optimizing the designs of the integrated circuits. We investigated the interdependence of various values of these parameters in the use over the set of test-bench circuits, as well as their influence on the quality of the final solution and the convergence speed. Due to the in...
متن کاملTuning Range Image Segmentation by Genetic Algorithm
Several range image segmentation algorithms have been proposed, each one to be tuned by a number of parameters in order to provide accurate results on a given class of images. Segmentation parameters are generally affected by the type of surfaces (e.g., planar versus curved) and the nature of the acquisition system (e.g., laser range finders or structured light scanners). It is impossible to an...
متن کاملGenetic Algorithm Framework for Application Tuning
class for measuring avoid permanent binding between abstraction and Genetic Algorithm Framework for Application Tuning Author: Cristian Ruican slide 14 / 45 implementation Source code available: http://www.cs.utt.ro/~crys/index_files/public/framework.zip Realizations Other GA Frameworks Name ComplexityData structure Architecture Abstract Comments views layers Galib high complex The library is n...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Chemical Engineering
سال: 2011
ISSN: 1687-806X,1687-8078
DOI: 10.1155/2011/646917