Ditapis dengan
Enhanced permeability prediction in porous media using particle swarm optimiz…
Accurately and efficiently predicting the permeability of porous media is essential for addressing a wide range of hydrogeological issues. However, the complexity of porous media often limits the effectiveness of individual prediction methods. This study introduces a novel Particle Swarm Optimization-based Permeability Integrated Prediction model (PSO-PIP), which incorporates a particle swarm o…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 12 hlm PDF, 9.874 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
A comparative analysis of super-resolution techniques for enhancing micro-CT …
High-resolution digital rock micro-CT images captured from a wide field of view are essential for various geosystem engineering and geoscience applications. However, the resolution of these images is often constrained by the capabilities of scanners. To overcome this limitation and achieve superior image quality, advanced deep learning techniques have been used. This study compares four differe…
- Edisi
- Vol.20, December 2023
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 17 hlm PDF, 6.377 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
A plugin for computing the pore/grain network tortuosity of a porous medium f…
Tortuosity is an important geometrical parameter of the pore or grain network in a porous medium. Here we present and discuss an implementation of a plugin to estimate the pore/grain network tortuosity of a porous medium sample. The tortuosity is estimated according to the geometric reconstruction algorithm that can be applied to 2D or 3D μCT image samples. To illustrate the tortuosity plugin …
- Edisi
- Vol.5, March 2020
- ISBN/ISSN
- 2590-1974
- Deskripsi Fisik
- 14 hlm PDF, 6.599 KB
- Judul Seri
- Applied Computing and Geoscience - Open Access
- No. Panggil
- 551.136
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