A Comparison of the Model Parameter Estimations from Self-Potential Anomalies by Levenberg-Marquardt (LM), Differential Evolution (DE) and Particle Swarm Optimization (PSO) Algorithms: An Example from Tamı¸s-Çanakkale, Turkey

Sındırgı P., Özyalın Ş.

Self-Potential Method: Theoretical Modeling and Applications in Geosciences, Biswas, Arkoprovo, Editör, Springer, London/Berlin , Chur, ss.133-153, 2021

  • Yayın Türü: Kitapta Bölüm / Araştırma Kitabı
  • Basım Tarihi: 2021
  • Yayınevi: Springer, London/Berlin 
  • Basıldığı Şehir: Chur
  • Sayfa Sayıları: ss.133-153
  • Editörler: Biswas, Arkoprovo, Editör
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

In geophysics, it is particularly important to choose an adequate optimization

algorithm for parameter estimation. In this study, the success of Levenberg-

Marquardt (LM), Differential Evolution (DE) and Particle Swarm Optimization

(PSO) inversion algorithms has been tested by applying to the synthetic and field

self-potential (SP) anomalies. Even though it is not preferred to compare derivativebased

algorithms with metaheuristics, thanks to a LM-based limitation procedure

first proposed in this study, a comparison could be realized. First, a synthetic SP

data have been inverted by LM, DE and PSO algorithms. Then, SP field data set

collected from Tamı¸s-Çanakkale, Turkey was evaluated by the same algorithms. The

estimated model parameters by these algorithms were compared with each other.

We also inverted vertical electrical sounding (VES) data set collected from the same

region, and an earth model was constructed by using both SP and VES methods.

The results from each geophysical method point out the same location for a fault.

Based on these studies, it can be concluded that DE, PSO, and LM algorithms may

be confidently used in SP modelling studies.