ESTIMATING THE PARAMETERS OF NONLINEAR REGRESSION MODELS THROUGH PARTICLE SWARM OPTIMIZATION

Volkan Soner Özsoy; H.Hasan Örkçü

Makale detayları

ESTIMATING THE PARAMETERS OF NONLINEAR REGRESSION MODELS THROUGH PARTICLE SWARM OPTIMIZATION

Yazarlar:

Volkan Soner Özsoy | H.Hasan Örkçü

Yayıncı:

Gazi University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Gazi University Journal of Science 2016 Vol.29 Issue 1, pp.187-199

Belge Tipi:

Makale

Yayın Tarihi:

3/2016

Belge Dili:

İngilizce

Document ID (Org No.):

2000428769

eISSN:

2147-1762

Özet:

 


Nonlinear regression models are widely used for modeling of stochastic phenomena and the estimating parameters problem plays a central role in the inference in nonlinear regression models. In this paper, this problem has been briefly discussed and an effective approach based on the Particle Swarm Optimization (PSO) algorithm is proposed in order to enhance the estimation accuracy. The PSO algorithm is tested on the well-known 28 nonlinear regression tasks of various level of difficulty. The results show that PSO approach which exhibits a rapid convergence to the minimum value of the sum of squared error function in less iterations, provides accurate estimates and is satisfactory for the parameter estimation of the nonlinear regression models.

.

Makale detayları

ESTIMATING THE PARAMETERS OF NONLINEAR REGRESSION MODELS THROUGH PARTICLE SWARM OPTIMIZATION

Yazarlar: Volkan Soner Özsoy | H.Hasan Örkçü

Yayıncı: Gazi University

Ana Başlıklar: Uygulamalı fizik

Dergi: Gazi University Journal of Science 2016 Vol.29 Issue 1, pp.187-199

Belge Tipi: Makale

Yayın Tarihi: 3/2016

Belge Dili: İngilizce

Document ID (Org No.): 2000428769

eISSN: 2147-1762

Sayı

Yazarlar:

Volkan Soner Özsoy | H.Hasan Örkçü

Yayıncı:

Gazi University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Gazi University Journal of Science 2016 Vol.29 Issue 1, pp.187-199

Belge Tipi:

Makale

Yayın Tarihi:

3/2016

Belge Dili:

İngilizce

Document ID (Org No.):

2000428769

eISSN:

2147-1762