A systematic review and future prospects of flood vulnerability indices

LL Moreira, MM de Brito… - Natural Hazards and …, 2021 - nhess.copernicus.org
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 …

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 …

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 …

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 …

[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 …

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 …

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 …

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 …

Revealing the structural behaviour of Brunelleschi's Dome with machine learning techniques

S Masini, S Bacci, F Cipollini, B Bertaccini - Data Mining and Knowledge …, 2024 - Springer
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 …

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 …