Akademik Veri Yönetim Sistemi
6th International Congress on Engineering and Life Science (ICELIS), Girne, Kıbrıs (Kktc), 2 - 04 Eylül 2025, ss.626-632, (Tam Metin Bildiri)
In geophysical engineering, the self-potential (SP) method is one of the most useful, simple, and applicable geophysical methods for various detecting and investigation applications in the subsurface. On the other hand, SP anomalies can be used in inversion studies to estimate the model parameters using derivative-based or metaheuristic algorithms. The literature on SP inversions with metaheuristic methods shows that many optimization algorithms are tested to determine their model parameters and show the algorithm's effectiveness. Moth-Flame Optimization (MFO) algorithm, a new and novel nature-inspired metaheuristic algorithm with accurate and reliable potential in engineering problems, is introduced to estimate the model parameters from synthetic and field SP anomalies. This study presents the first implementation of the MFO algorithm for inversion of SP anomalies in geophysics. The algorithm was developed in R programming. The test studies with the synthetic data included the cases of noise-free and noisy data. Additionally, the Arizona (USA) anomaly was tested as field data. According to the inversion results of SP anomalies, the MFO algorithm can be used as an efficient and accurate method for the inversion of SP anomalies.