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Journals / Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi / 2026 / Cilt: 28 Sayı: 84

Estimation of Model Parameters from Self-Potential Anomalies Generated by Simple-Geometric Shaped Structures Using Bat Algorithm

Doğal Potansiyel Anomalilerini Oluşturan Basit Geometrik Şekilli Yapılarda Yarasa Algoritması Kullanılarak Model Parametre Kestirimi

Seçil Turan Karaoğlan(DOKUZ EYLÜL ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ)0000-0002-3871-4792
Gökhan Göktürkler(DOKUZ EYLÜL ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ)0000-0002-2842-0766
Sanam Hosseinzadeh(DOKUZ EYLÜL ÜNİVERSİTESİ, FEN BİLİMLERİ ENSTİTÜSÜ)0000-0002-3486-4689
Pages
449–461
Publication Date
2026-09-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

By comparing the inversion results of the theoretical data with the true values of the data, and the inversion results of the field data with the results of other studies in the literature, it was shown that the Bat Algorithm is applicable as an effective method for the inversion of self-potential data.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Metaheuristic methods have started to be preferred instead of derivative-based optimization methods for the inversion of geophysical data.
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Key Findings & Data:Metaheuristic methods, inspired by nature, are used in geophysical inversion studies because of their advantages such as comprehensive exploring of the search space, the non-necessity of a good initial model, and easy adaptability to every optimization problem.
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Conclusion & Impact:By comparing the inversion results of the theoretical data with the true values of the data, and the inversion results of the field data with the results of other studies in the literature, it was shown that the Bat Algorithm is applicable as an effective method for the inversion of self-potential data.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Yarasa Algoritması · Metasezgisel · Doğal Potansiyel Anomalisi

Abstract

Metaheuristic methods have started to be preferred instead of derivative-based optimization methods for the inversion of geophysical data. Metaheuristic methods, inspired by nature, are used in geophysical inversion studies because of their advantages such as comprehensive exploring of the search space, the non-necessity of a good initial model, and easy adaptability to every optimization problem. In this study, the investigations are presented for the inversion of Self-Potential data using the Bat Algorithm, which is a population-based metaheuristic method. First, parameter tuning studies of the Bat Algorithm were carried out, and the control parameters determined from the tuning were used for the inversion of theoretical noise-free and noisy Self-Potential data, as well as two field data sets. Additionally, the estimated parameters were statistically tested by using the Metropolis-Hasting algorithm to determine the reliability of the model parameters of the theoretical and field data. By comparing the inversion results of the theoretical data with the true values of the data, and the inversion results of the field data with the results of other studies in the literature, it was shown that the Bat Algorithm is applicable as an effective method for the inversion of self-potential data.

Özet

Jeofizik verilerinin ters çözümünde günümüzde türev tabanlı optimizasyon yöntemlerinin yerini metasezgisel yöntemler almaya başlamıştır. Arama uzayını kapsamlı taraması, iyi bir başlangıç modeline ihtiyaç duymaması ve her optimizasyon problemine kolay uyarlanabilmesi gibi avantajları nedeniyle doğadan esinlenerek oluşturulan birçok metasezgisel yöntem, jeofizik ters çözüm çalışmalarında kullanılmaktadır. Bu çalışmada, popülasyon tabanlı bir metasezgisel yöntem olan Yarasa Algoritmasının doğal potansiyel verilerinin ters çözümünde kullanımına yönelik incelemeler sunulmuştur. Öncelikle Yarasa Algoritmasının kontrol parametrelerini belirleme çalışmaları yapılmış, elde edilen kontrol parametreleri kullanılarak da gürültüsüz ve gürültü eklenmiş kuramsal doğal potansiyel verilerinin ve iki adet arazi verisinin ters çözümü çalışmaları gerçekleştirilmiştir. Ayrıca, kuramsal ve arazi verilerine ait model parametrelerinin güvenilirliğinin belirlenmesi amacıyla Metropolis-Hasting algoritması kullanılarak, kestirim parametrelerinin olasılık yoğunluğu histogramları, istatistiksel olarak da test edilmiştir. Kuramsal verilerin ters çözüm sonuçları ilgili verilere ait doğru değerlerle, arazi verilerine ait ters çözüm sonuçlarıysa literatürdeki diğer çalışmalarda bulunan sonuçlarla kıyaslanarak Yarasa Algoritmasının doğal potansiyel verilerinin ters çözümünde efektif bir yöntem olarak uygulanabilir olduğu görülmüştür

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Cite This Article

Karaoğlan, S. T., Göktürkler, G., Hosseinzadeh, S. (2026). Estimation of Model Parameters from Self-Potential Anomalies Generated by Simple-Geometric Shaped Structures Using Bat Algorithm. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi, Cilt: 28 Sayı: 84, 449–461. https://doi.org/10.21205/deufmd.2026288412

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