Ditapis dengan
Noise Elimination for Wide Field Electromagnetic Data via Improved Dung Beetl…
Noise profoundly affects the quality of electromagnetic data, and selecting the appropriate hyperparameters for machine learning models poses a significant challenge. Consequently, the current machine learning denoising techniques fall short in delivering precise processing of Wide Field Electromagnetic Method (WFEM) data. To eliminate the noise, this paper presents an electromagnetic data deno…
- Edisi
- Vol.15, Issue 1, January 2025
- ISBN/ISSN
- 2076-3263
- Deskripsi Fisik
- 21 hlm PDF, 3,240 KB
- Judul Seri
- Geosciences
- No. Panggil
- 550
Transfer learning for well logging formation evaluation using similarity weights
Machine learning has been widely applied in well logging formation evaluation studies. However, several challenges negatively impacted the generalization capabilities of machine learning models in practical implementations, such as the mismatch of data domain between training and testing datasets, imbalances among sample categories, and inadequate representation of data model. These issues have…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 16 hlm PDF, 22.2488 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
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