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A systematic review and future prospects of flood vulnerability indices
This paper provides a state-of-art account on flood vulnerability indices, highlighting
worldwide trends and future research directions. A total of 95 peer-reviewed articles …
worldwide trends and future research directions. A total of 95 peer-reviewed articles …
A review on intelligent recognition with logging data: tasks, current status and challenges
X Zhu, H Zhang, Q Ren, L Zhang, G Huang… - Surveys in …, 2024 - Springer
Geophysical logging series are valuable geological data that record the physical and
chemical information of borehole walls and in-situ formations, and are widely used by …
chemical information of borehole walls and in-situ formations, and are widely used by …
Coupled retrieval of heavy metal nickel concentration in agricultural soil from spaceborne hyperspectral imagery
Y Sun, S Chen, X Dai, D Li, H Jiang, K Jia - Journal of Hazardous Materials, 2023 - Elsevier
Widespread soil contamination endangers public health and undermines global attempts to
achieve the United Nations Sustainable Development Goals. Due to the lack of relevant …
achieve the United Nations Sustainable Development Goals. Due to the lack of relevant …
Debris-flow susceptibility assessment in Dongchuan using stacking ensemble learning including multiple heterogeneous learners with RFE for factor optimization
K Li, J Zhao, Y Lin - Natural Hazards, 2023 - Springer
An accurate assessment of debris-flow susceptibility is of great importance to the prevention
and control of debris-flow disasters in mountainous areas. In this study, by applying the …
and control of debris-flow disasters in mountainous areas. In this study, by applying the …
[HTML][HTML] A deep kernel method for lithofacies identification using conventional well logs
SQ Dong, ZH Zhong, XH Cui, LB Zeng, X Yang, JJ Liu… - Petroleum Science, 2023 - Elsevier
How to fit a properly nonlinear classification model from conventional well logs to lithofacies
is a key problem for machine learning methods. Kernel methods (eg, KFD, SVM, MSVM) are …
is a key problem for machine learning methods. Kernel methods (eg, KFD, SVM, MSVM) are …
Systematic investigation of keywords selection and processing strategy on search engine forecasting: A case of tourist volume in Bei**g
Z Yuan, G Jia - Information Technology & Tourism, 2022 - Springer
The timeliness, precision, and low cost of search data have great potential for projecting
tourist volume. Obtaining valuable information for decision-making, particularly for …
tourist volume. Obtaining valuable information for decision-making, particularly for …
Empirical analysis of sensor type importance for data preparation of real-time operational status monitoring in fused deposition modeling 3D printers
S Baek, BS Kim, Y Lee - The International Journal of Advanced …, 2024 - Springer
The fused deposition modeling (FDM)-type three-dimensional (3D) printer is a popular
choice in manufacturing facilities due to its capability of printing complex-shaped objects …
choice in manufacturing facilities due to its capability of printing complex-shaped objects …
Unsupervised fault detection in automated sequential manufacturing processes through image analysis and convolutional LSTM-based next visual status prediction
NH Yu, S Baek - The International Journal of Advanced Manufacturing …, 2024 - Springer
With the advancement of information and communication technology, the integration of
smart systems into discrete sequential processes has been realized in manufacturing …
smart systems into discrete sequential processes has been realized in manufacturing …
Revealing the structural behaviour of Brunelleschi's Dome with machine learning techniques
Abstract The Brunelleschi's Dome is one of the most iconic symbols of the Renaissance and
is among the largest masonry domes ever constructed. Since the late 17th century, first …
is among the largest masonry domes ever constructed. Since the late 17th century, first …
Short-term power load forecasting model based on t-SNE dimension reduction visualization analysis, VMD and LSSVM improved with chaotic sparrow search …
L Wang, T Tian, H Xu, H Tong - Journal of Electrical Engineering & …, 2022 - Springer
The stable operation of power system has the strong constraint of load balance. Accurate
power load forecasting is of great significance in ensuring power system planning and …
power load forecasting is of great significance in ensuring power system planning and …