Callisto, Dheo (2023) Performa Gazelle Optimization Algorithm dalam Inversi Parameter Model Data Magnetik. Other thesis, Institut Teknologi Sepuluh Nopember.
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01111940000054-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only until 1 September 2025. Download (7MB) | Request a copy |
Abstract
Pemodelan inversi merupakan proses pada pengolahan data geofisika untuk interpretasi struktur bawah permukaan dengan inversi data lapangan menjadi model-model yang bersesuaian dengan kondisi geologis untuk keperluan penelitian dan interpretasi. Pada penelitian ini, data anomali magnetik diinversi menggunakan algoritma yang sebelumnya belum pernah digunakan untuk inversi data magnetik, yaitu Gazelle Optimization Algorithm (GOA). GOA merupakan sebuah algoritma optimasi baru yang masih belum banyak digunakan untuk permasalahan inversi geofisika. Pada penelitian ini, GOA digunakan untuk menyelesaikan permasalahan inversi data magnetik sintetik dengan jumlah anomali tunggal dan anomali jamak serta data lapangan. Dalam pelaksanaannya, GOA dibandingkan dengan algoritma-algoritma lain yang telah digunakan dalam inversi data magnetik, yaitu differential search algorithm (DSA), manta ray foraging optimization (MRFO), bat algorithm (BA), very fast simulated annealing (VFSA), dan barnacles mating optimizer (BMO). Hasilnya menunjukkan bahwa GOA memiliki performa yang cukup baik untuk permasalahan inversi data magnetik.
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Inversion modelling is a process in geophysical data processing in the interpretation of sub-surface structures, where field data is inversed into geological models for research and interpretation purposes. In this research, the magnetic anomaly data will be inversed using an algorithm that has not previously been used for magnetic data inversion, namely the Gazelle Optimisation Algorithm (GOA). GOA is a new optimisation algorithm that has not been widely used for geophysical inversion problems. In this research, GOA is used to solve the inversion problem of synthetic magnetic data with the number of single anomalies and multiple anomalies and field data. In its implementation, GOA will be compared with other algorithms that have been used in the inversion of magnetic data, namely differential search algorithm (DSA), manta ray foraging optimisation (MRFO), bat algorithm (BA), very fast simulated annealing (VFSA), and barnacles mating optimizer (BMO). The results show that GOA can provide reliable and excellent results for inverting model parameters from magnetic data.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Algoritma, Inversi, Magnetik; Algorithm, Inversion, Magnetic |
| Subjects: | Q Science > QA Mathematics > QA9.58 Algorithms Q Science > QC Physics T Technology > T Technology (General) > T57.84 Heuristic algorithms. T Technology > TN Mining engineering. Metallurgy > TN269 Prospecting--Geophysical methods |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Physics > 45201-(S1) Undergraduate Thesis |
| Depositing User: | Dheo Callisto Furi |
| Date Deposited: | 02 Oct 2023 06:14 |
| Last Modified: | 02 Oct 2023 06:14 |
| URI: | http://repository.its.ac.id/id/eprint/103322 |
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