Parameter estimation in mathematical models using the real coded genetic algorithms

Tutkun N.

Expert Systems with Applications, cilt.36, sa.2 PART 2, ss.3342-3345, 2009 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 36 Sayı: 2 PART 2
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1016/j.eswa.2008.01.060
  • Dergi Adı: Expert Systems with Applications
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.3342-3345
  • Anahtar Kelimeler: Binary coded genetic algorithms, Dynamic system identification, Nonlinear curve fitting, Ordinary differential equations, Parameter estimation, Real coded genetic algorithms
  • İstanbul Ticaret Üniversitesi Adresli: Hayır

Özet

In this study, parameter estimation in mathematical models using the real coded genetic algorithms (RCGA) approach is presented. Although the RCGA is similar with the binary coded genetic algorithms (BCGA) in terms of genetic process, it has few advantages such as high precision, non-existence of Hamming's cliff etc., over the BCGA. In this approach, creating initial population and selection procedure are almost the same with the BCGA, but crossover and mutation operations. The proposed approach is implemented on the second order ordinary differential equations modeling the enzyme effusion problem and it is compared with previous approaches. The results indicate that the proposed approach produced better estimated results with respect to previous findings. © 2008 Elsevier Ltd. All rights reserved.