The adaptive extended kalman filter approach for the Lotka-Volterra model and application to economic variables

ÖZBEK L., HACIOĞLU V.

Sigma Journal of Engineering and Natural Sciences, cilt.42, sa.2, ss.390-398, 2024 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 42 Sayı: 2
  • Basım Tarihi: 2024
  • Doi Numarası: 10.14744/sigma.2024.00037
  • Dergi Adı: Sigma Journal of Engineering and Natural Sciences
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, Academic Search Premier, Directory of Open Access Journals
  • Sayfa Sayıları: ss.390-398
  • Anahtar Kelimeler: Extended Kalman Filter, Lotka-Volterra Model, Parameters Estimation
  • Ankara Üniversitesi Adresli: Evet

Özet

The main aim of this article is to extend on the application of the grey Lotka-Volterra model by Wu et al. [1] with a linear programming method. We used this method for estimating the parameters of behavioral variables under the criterion of the minimization of mean absolute percentage error (MAPE). Our empirical analysis indicates that the adaptive extended Kalman filter (EKF) approach performs far better compared to traditional Lotka-Volterra model in the prediction of the relevant parameters. Comparisons of empirical results with the linear programming method for parameter estimation of the grey Lotka-Volterra model demonstrate that the EKF approach has more powerful and efficient prediction performance.