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The gradient boosting decision tree is a well-known machine learning algorithm. Despite
numerous advancements in its application, its efficiency still needs to be improved for large …

Išsaugoti Cituoti Cituoja 56 Susiję straipsniai Visos 3 versijos

Intelligent map** of geochemical anomalies: Adaptation of DBSCAN and mean-shift clustering approaches

M Hajihosseinlou, A Maghsoudi… - Journal of Geochemical …, 2024 - Elsevier

Cluster analysis can be used to organize samples and generate ideas regarding the
multivariate geochemistry of given dataset. Traditional clustering techniques have the …

Išsaugoti Cituoti Cituoja 31 Susiję straipsniai Visos 2 versijos

Random-drop data augmentation of deep convolutional neural network for mineral prospectivity map**

T Li, R Zuo, Y **ong, Y Peng - Natural Resources Research, 2021 - Springer

Convolutional neural network (CNN) has demonstrated promising performance in
classification and prediction in various fields. In this study, a CNN is used for mineral …

Išsaugoti Cituoti Cituoja 137 Susiję straipsniai Visos 4 versijos

Detection of the multivariate geochemical anomalies associated with mineralization using a deep convolutional neural network and a pixel-pair feature method

C Zhang, R Zuo, Y **ong - Applied Geochemistry, 2021 - Elsevier

Abstract Machine learning (ML) algorithms are widely applied in various fields owing to their
strong ability to abstract high-level features from a large number of training samples …

Išsaugoti Cituoti Cituoja 85 Susiję straipsniai Visos 4 versijos

A physically constrained hybrid deep learning model to mine a geochemical data cube in support of mineral exploration

R Zuo, Y Xu - Computers & Geosciences, 2024 - Elsevier

Geochemical survey data provide rich information on geochemical elemental concentrations
and their spatial patterns in relation to mineralization or pollution. A geochemical data cube …

Išsaugoti Cituoti Cituoja 21 Susiję straipsniai Visos 3 versijos

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Metallogenic-factor variational autoencoder for geochemical anomaly detection by ad-hoc and post-hoc interpretability algorithms

Z Luo, R Zuo, Y **ong, B Zhou - Natural Resources Research, 2023 - Springer

Deep learning algorithms (DLAs) are becoming hot tools in processing geochemical survey
data for mineral exploration. However, it is difficult to understand their working mechanisms …

Išsaugoti Cituoti Cituoja 26 Susiję straipsniai Visos 4 versijos

Robust feature extraction for geochemical anomaly recognition using a stacked convolutional denoising autoencoder

Y **ong, R Zuo - Mathematical Geosciences, 2022 - Springer

Deep neural networks perform very well in learning high-level representations in support of
multivariate geochemical anomaly recognition. Geochemical exploration data typically …

Išsaugoti Cituoti Cituoja 78 Susiję straipsniai Visos 3 versijos

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