Quantification of model uncertainty and variability for landslide displacement prediction based on Monte Carlo simulation

L Wang, T Xiao, S Liu, W Zhang, B Yang, L Chen - Gondwana Research, 2023 - Elsevier
Reliable and accurate prediction of landslide displacement is essential for early warning
systems, as well as for disaster prevention and mitigation. Machine learning and deep …

[HTML][HTML] Mitigating uncertainties in mineral exploration targeting: Majority voting and confidence index approaches in the context of an exploration information system …

M Yousefi, MD Lindsay, O Kreuzer - Ore Geology Reviews, 2024 - Elsevier
Various mineral prospectivity modelling (MPM) approaches are available for targeting
mineral deposits, each method capable of predicting areas of high prospectivity. Given the …

[HTML][HTML] Decision-making within geochemical exploration data based on spatial uncertainty–A new insight and a futuristic review

B Sadeghi, DR Cohen - Ore Geology Reviews, 2023 - Elsevier
In mineral prospectivity mapping, limitations in the density of geochemical sampling that can
be collected across a region may generate the need for interpolation of data between …

3-D Structural geological models: Concepts, methods, and uncertainties

F Wellmann, G Caumon - Advances in geophysics, 2018 - Elsevier
The Earth below ground is the subject of interest for many geophysical as well as geological
investigations. Even though most practitioners would agree that all available information …

Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid …

M Abbaszadeh, S Soltani-Mohammadi… - Computers & …, 2022 - Elsevier
The support vector classifier (SVC) is one of the most powerful machine learning algorithms.
This algorithm has been accepted as an effective method in three-dimensional geological …

[HTML][HTML] Multi-level voxel representations for digital twin models of tunnel geological environment

H Wu, Q Zhu, Y Guo, W Zheng, L Zhang… - International Journal of …, 2022 - Elsevier
Intelligent tunnel engineering requires accurate and comprehensive digital twin models to
represent complex geological environments. The digital twin model of tunnel geological …

3D geological structure inversion from Noddy-generated magnetic data using deep learning methods

J Guo, Y Li, MW Jessell, J Giraud, C Li, L Wu, F Li… - Computers & …, 2021 - Elsevier
Using geophysical inversion for three-dimensional (3D) geological modeling is an effective
way to model underground geological structures. In this study, we propose and investigate a …

Multi-view spectral clustering for uncertain objects

KK Sharma, A Seal - Information Sciences, 2021 - Elsevier
In the machine learning and pattern recognition fraternity, uncertain data clustering is an
essential job because uncertainty in data makes the clustering process more difficult …

Outlier-robust multi-view clustering for uncertain data

KK Sharma, A Seal - Knowledge-Based Systems, 2021 - Elsevier
Nowadays, multi-view clustering is drawn more and more attention in the area of machine
learning because real-world datasets frequently consist of multiple views. Moreover, it …

A simulation-based framework for modulating the effects of subjectivity in greenfield mineral prospectivity mapping with geochemical and geological data

M Parsa, AB Pour - Journal of Geochemical Exploration, 2021 - Elsevier
Abstract Mineral Prospectivity Mapping (MPM) is a multifaceted process relying heavily on
experts' judgments. Notwithstanding the importance of human interpretations and cognitive …