CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Evaluation of Cuckoo Search Usage for Model Parameters Estimation

by Walid M. Aly
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 78 - Number 11
Year of Publication: 2013
Authors: Walid M. Aly
10.5120/13530-1072

Walid M. Aly . Evaluation of Cuckoo Search Usage for Model Parameters Estimation. International Journal of Computer Applications. 78, 11 ( September 2013), 1-6. DOI=10.5120/13530-1072

@article{ 10.5120/13530-1072,
author = { Walid M. Aly },
title = { Evaluation of Cuckoo Search Usage for Model Parameters Estimation },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 78 },
number = { 11 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume78/number11/13530-1072/ },
doi = { 10.5120/13530-1072 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:51:16.018928+05:30
%A Walid M. Aly
%T Evaluation of Cuckoo Search Usage for Model Parameters Estimation
%J International Journal of Computer Applications
%@ 0975-8887
%V 78
%N 11
%P 1-6
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cuckoo Search is gaining a lot of attention as a new soft computing technique inspired by nature,in this research the application of Cuckoo Search for solving the problem of estimating the parameters of a nonlinear model is investigated from both aspects of efficiency and robustness. Using a case study of estimation of parameters of a nonlinear model for the cutting tool temperature in an industrial metal cutting system, Cuckoo search was proved to be efficient in comparison to other approaches like genetic algorithms and particle swarm optimization. The paper also investigates the sensitivity of the Cuckoo Search performance to the variation of its tuning parameters, results showed the high efficiency and robustness of Cuckoo Search when applied to the problem of parameter estimation of a nonlinear model.

References
  1. Nasko Atanasov and Alexandar Ichtev. Closed-loop system identification with recursive modifications of the instrumental variable method. Informatica, 22(2):165–176, April 2011.
  2. A. T. Fleury, F. C. Trigo, and F. P. R. Martins. A new approach based on computer vision and non-linear kalman filtering to monitor the nebulization quality of oil flames. Expert Syst. Appl. , 40(12):4760–4769, September 2013.
  3. I. Kamkar, M. -R. Akbarzadeh-T, and M. Yaghoobi. Intelligent water drops a new optimization algorithm for solving the vehicle routing problem. In Systems Man and Cybernetics (SMC), 2010 IEEE International Conference on, pages 4142– 4146, 2010.
  4. Sameh Kessentini, Dominique Barchiesi, Thomas Grosges, Laurence Giraud-Moreau, and Marc Lamy de la Chapelle. Adaptive non-uniform particle swarm application to plasmonic design. Int. J. Appl. Metaheuristic Comput. , 2(1):18– 28, January 2011.
  5. Yang Liu and Fan Sun. Parameter estimation of a pressure swing adsorption model for air separation using multiobjective optimisation and support vector regression model. Expert Syst. Appl. , 40(11):4496–4502, September 2013.
  6. Gin´es Moreno and Vicente Pascual. Programming with fuzzy logic and mathematical functions. In Proceedings of the 6th international conference on Fuzzy Logic and Applications, WILF'05, pages 89–98, Berlin, Heidelberg, 2006. Springer- Verlag.
  7. Triet Nguyen-Van and N. Hori. New class of discrete-time models for non-linear systems through discretisation of integration gains. Control Theory Applications, IET, 7(1):80–89, 2013.
  8. M. Papoutsidakis, G. Gkafas, S. Kanavetas, and G. Chamilothoris. Modeling and simulated control of non-linear switching actuation systems. In Proceedings of the 8th WSEAS international conference on System science and simulation in engineering, ICOSSSE '09, pages 97–102,Stevens Point, Wisconsin, USA, 2009. World Scientific and Engineering Academy and Society (WSEAS).
  9. Dongyong Yang, Jinyin Chen, and N. Matsumoto. Particle swarm optimization with adaptive parameters. In Software Engineering, Artificial Intelligence, Networking, and Parallel/ Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference on, volume 1, pages 616–621, 2007.
  10. Xin-She Yang. Nature-Inspired Metaheuristic Algorithms. Luniver Press, 2008.
  11. Xin-She Yang. Metaheuristic algorithms for self-organizing systems: A tutorial. In Self-Adaptive and Self-Organizing Systems (SASO), 2012 IEEE Sixth International Conference on, pages 249–250, 2012.
  12. Xin-She Yang and S. Deb. Cuckoo search via levy flights. In Nature Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on, pages 210–214, 2009.
  13. Liu Yi-jian, Zhang Jian-ming, and Wang Shu-qing. Parameter estimation of cutting tool temperature nonlinear model using pso algorithm. Journal of Zhejiang University Science A, 6(10):1026–1029, 2005.
  14. J. X. Zhou. Ga algorithm for cutting experiment data drawing. Journal of Southwest Petroleum Institute, 29(3):1062–63, 1998.
Index Terms

Computer Science
Information Sciences

Keywords

Cuckoo Search Parameter estimation Nonlinear systems

Powered by PhDFocusTM