Backtracking Search Optimization: A Novel Global Optimization Algorithm for the Inversion of Gravity Anomalies

Ekinci, Yunus Levent; Balkaya, Çağlayan; Göktürkler, Gökhan

doi:10.1007/s00024-021-02855-3

Cited by 12 publications

(10 citation statements)

References 44 publications

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“…It must be noted that there is no algorithm-based control parameter value that can be successful for all types of inverse problems. These optimal values may vary depending on the nature of inverse problems 49 , 70 , 75 . Hence, a vital step of applying a metaheuristic effectively is to appropriately determine the best user-defined control parameter value/s.…”

Section: Synthetic Applicationsmentioning

confidence: 99%

“…Model analysis of the objective function. The ill-posedness characteristics of the geophysical inverse problem makes the model parameter estimation process suspect and error-prone 70,71 . Hence, pre-and postinversion uncertainty appraisal studies play a crucial role in the detection of the ambiguities and consistencies in the obtained source parameters 36 .…”

Section: Synthetic Applicationsmentioning

confidence: 99%

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Magnetic anomaly inversion through the novel barnacles mating optimization algorithm

Essa

Ekinci

et al. 2022

Sci Rep

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Dealing with the ill-posed and non-unique nature of the non-linear geophysical inverse problem via local optimizers requires the use of some regularization methods, constraints, and prior information about the Earth's complex interior. Another difficulty is that the success of local search algorithms depends on a well-designed initial model located close to the parameter set providing the global minimum. On the other hand, global optimization and metaheuristic algorithms that have the ability to scan almost the entire model space do not need an assertive initial model. Thus, these approaches are increasingly incorporated into parameter estimation studies and are also gaining more popularity in the geophysical community. In this study we present the Barnacles Mating Optimizer (BMO), a recently proposed global optimizer motivated by the special mating behavior of barnacles, to interpret magnetic anomalies. This is the first example in the literature of BMO application to a geophysical inverse problem. After performing modal analyses and parameter tuning processes, BMO has been tested on simulated magnetic anomalies generated from hypothetical models and subsequently applied to three real anomalies that are chromite deposit, uranium deposit and Mesozoic dike. A second moving average (SMA) scheme to eliminate regional anomalies from observed anomalies has been examined and certified. Post-inversion uncertainty assessment analyses have been also implemented to understand the reliability of the solutions achieved. Moreover, BMO’s solutions for convergence rate, stability, robustness and accuracy have been compared with the solutions of the commonly used standard Particle Swarm Optimization (sPSO) algorithm. The results have shown that the BMO algorithm can scan the model parameter space more extensively without affecting its ability to consistently approach the unique global minimum in this presented inverse problem. We, therefore, recommend the use of competitive BMO in model parameter estimation studies performed with other geophysical methods.

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Section: Synthetic Applicationsmentioning

confidence: 99%

Section: Synthetic Applicationsmentioning

confidence: 99%

Magnetic anomaly inversion through the novel barnacles mating optimization algorithm

Essa

Ekinci

et al. 2022

Sci Rep

Self Cite

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“…Fine‐tuned parameters can increase the efficiency of the algorithm. Therefore, to obtain the best performance of an optimizer, tuning studies should be performed with a synthetic data set and the optimal values should be determined before inversion of real data sets (Ç. Balkaya et al., 2017; Ekinci, Balkaya, & Göktürkler, 2021; Fernández‐Martínez et al., 2010; Pace et al., 2019; Pallero et al., 2017). Tuning tests were performed with the synthetic geomagnetic anomaly produced for the modal analysis.…”

Section: Methodsmentioning

confidence: 99%

Inversion of Geomagnetic Anomalies Caused by Ore Masses Using Hunger Games Search Algorithm

Ai,

Ekinci,

Balkaya

et al. 2023

Earth and Space Science

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Geomagnetic anomaly interpretation through inversion procedures often yields useful results in determining the key details of ore masses. However, the problem is complicated due to the known ambiguous phenomena of the inversion process. Thus, details such as location, depth and shape can only be estimated using an efficient algorithm. To this end, we presented here a novel global optimization algorithm called Hunger Games Search (HGS) for the inversion of geomagnetic anomalies caused by ore masses. HGS is a well‐organized metaheuristic inspired by the hunger‐driven instincts and social behavioral decisions of animals. This is the first work in the literature to introduce this optimizer for the inversion of geophysical anomalies. We revealed the model parameter dependencies and the optimum control parameter values of the algorithm by performing some modal analyses and parameter tuning studies, respectively. The capability of HGS was demonstrated on synthetically produced geomagnetic responses and on three real anomalies obtained from some exploration fields in India and the USA. Uncertainty appraisal studies showed the solidity of the outputs of the algorithm. Moreover, some comparative studies with the fine‐tuned standard Particle Swarm Optimization, a commonly used tool for the inversion of geophysical anomalies, indicated that HGS algorithm provides better results in terms of convergence characteristics and solution stabilities in the presented inverse problem. We therefore recommend the use of this metaheuristic in model parameter estimation studies when dealing with this kind of geophysical potential field problems.

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“…Jeofizikte parametre kestirim çalışmalarında yaygın olarak kullanılan algoritmalara ise GA [10][11][12], PSO [13][14][15][16][17][18][19], FE [2,3,[19][20][21][22][23][24], YIİ algoritması [25][26][27][28][29] farksal arama algoritması [30,31] örnek olarak verilebilir. Parametre kestirim çalışmalarında uygulanan güncel algoritmalara örnekler ise gri kurt optimizasyonu [32] geri-izleme arama optimizasyonu [33], guguk kuşu arama algoritması [34] olarak verilebilir.…”

Section: Introductionunclassified

Inversion of Gravity Anomalies by Cuckoo Search Algorithm

KARAOĞLAN>

Göktürkler

2022

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Metasezgisel algoritmalar jeofizik ters çözüm çalışmalarında sıklıkla kullanılır duruma gelmiştir. Türev tabanlı en iyileme yöntemlerinin aksine, iyi bir başlangıç modeline ihtiyaç duymayan arama algoritmaları parametre uzayını kapsamlı tarama özelliğine sahip olduklarından jeofizikte model parametre kestirimleri için avantaj sağlamaktadır. Sunulan çalışmada, gravite anomalilerinin ters çözümünde guguk kuşu arama algoritması kullanılmıştır. Algoritmanın kullanıcı tanımlı parametre sayısının az olması ve yapılan literatür taramasında doğadan esinlenilerek oluşturulan birçok metasezgisel yönteme göre daha iyi sonuç vermesi, parametre kestirim çalışmasında guguk kuşu algoritmasının kullanılmasını teşvik etmektedir. Gravite belirtisine ait genlik katsayısı, kaynak derinliği, belirti izdüşümü ve şekil faktörleri kestirimi yapılan model parametreleridir. Algoritmaya ait kontrol parametreleri (popülasyon sayısı ve yumurtanın yuvadan atılma olasılığı) ise gürültüsüz kuramsal veri kümesi kullanılarak parametre belirleme çalışmaları (parameter tuning) ile detaylı bir şekilde irdelenmiştir. Sonrasında kontrol parametre çiftinin doğruluğu gürültü içeren veri kümesi üzerinde test edilmiştir. Ardından, Küba’da bir kromit yatağı üzerinde ölçülen arazi verisi ve Kanada’da yer alan bir sülfit cevheri üzerinde ölçülen arazi verisi değerlendirilerek, anomalilere ait model parametreleri kestirilmiştir. Kuramsal ve arazi veri kümelerine ait model parametrelerinin güvenilirliğinin belirlenmesi için, Metropolis-Hasting algoritması kullanılarak, kestirim parametreleri istatistiksel olarak da test edilmiştir. Doğası gereği iyi bir başlangıç modeline ve model parametrelerine göre kısmi türev hesabına ihtiyaç duymayan algoritma, kullanıcı tanımlı iki parametre içermesi sayesinde parametre kestirim çalışmalarında kolaylık sağlamıştır. Yapılan belirsizlik analizleri sonucunda da algoritmanın gravite verilerinin ters çözümünde uygulanabilir bir algoritma olduğu belirlenmiştir.

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Backtracking Search Optimization: A Novel Global Optimization Algorithm for the Inversion of Gravity Anomalies

Cited by 12 publications

References 44 publications

Magnetic anomaly inversion through the novel barnacles mating optimization algorithm

Magnetic anomaly inversion through the novel barnacles mating optimization algorithm

Inversion of Geomagnetic Anomalies Caused by Ore Masses Using Hunger Games Search Algorithm

Inversion of Gravity Anomalies by Cuckoo Search Algorithm

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