Ensemble learning for remaining fatigue life prediction of structures with stochastic parameters: a data-driven approach
An effective approach is proposed to predict the remaining fatigue life (RFL) of structures
with stochastic parameters. The extended finite element method (XFEM) was firstly used to …
with stochastic parameters. The extended finite element method (XFEM) was firstly used to …
Automatic prognosis of lung cancer using heterogeneous deep learning models for nodule detection and eliciting its morphological features
W Wang, G Charkborty - Applied Intelligence, 2021 - Springer
Among cancers, lung cancer has the highest morbidity, and mortality rate. The survival
probability of lung cancer patients depends largely on an early diagnosis. For predicting …
probability of lung cancer patients depends largely on an early diagnosis. For predicting …
Assessing wetland habitat vulnerability in moribund Ganges delta using bivariate models and machine learning algorithms
S Pal, S Paul - Ecological Indicators, 2020 - Elsevier
The present study aims to measure wetland habitat vulnerability (WHV) in moribund deltaic
part of India using ten conditioning parameters eg, WPF, water depth, change in WPF …
part of India using ten conditioning parameters eg, WPF, water depth, change in WPF …
Pneumonia screening on chest X-rays with optimized ensemble model
S Nalluri, R Sasikala - Expert Systems with Applications, 2024 - Elsevier
Pneumonia is a lung illness that may result from a variety of various viral diseases and may
be lethal. It might be difficult to diagnose and treat pneumonia on chest X-ray pictures …
be lethal. It might be difficult to diagnose and treat pneumonia on chest X-ray pictures …
Tri-regularized nonnegative matrix tri-factorization for co-clustering
The objective of co-clustering is to simultaneously identify blocks of similarity between the
sample set and feature set. Co-clustering has become a widely used technique in data …
sample set and feature set. Co-clustering has become a widely used technique in data …
Enhancing nonlinear dynamics analysis of railway vehicles with artificial intelligence: a state-of-the-art review
Z Tang, Y Hu, Z Qu - Nonlinear Dynamics, 2024 - Springer
Railway vehicle dynamics involves modelling, simulating, and analysing the motion and
interaction of rail vehicles under external force, exhibiting numerous nonlinear behaviours …
interaction of rail vehicles under external force, exhibiting numerous nonlinear behaviours …
Convolution-based linear discriminant analysis for functional data classification
GEC Guzman, A Fujita - Information Sciences, 2021 - Elsevier
Technological advances have allowed for the rise in more reliable and less expensive
sensors to collect data over time (eg, on temperature, heartbeat, and neural activity) …
sensors to collect data over time (eg, on temperature, heartbeat, and neural activity) …
Nonlinear fault detection for batch processes via improved chordal kernel tensor locality preserving projections
Y Zhou, K Xu, F He, D He - Control Engineering Practice, 2020 - Elsevier
The quality and stability of products are seriously influenced by the process conditions. A
large number of modern production processes can be considered as batch processes, with …
large number of modern production processes can be considered as batch processes, with …
Robust deep fuzzy K-means clustering for image data
X Wu, YF Yu, L Chen, W Ding, Y Wang - Pattern Recognition, 2024 - Elsevier
Image clustering is a difficult task with important application value in computer vision. The
key to this task is the quality of images features. Most of current clustering methods …
key to this task is the quality of images features. Most of current clustering methods …
A model for generating workplace procedures using a CNN-SVM architecture
J Patalas-Maliszewska, D Halikowski - Symmetry, 2019 - mdpi.com
(1) Background: Improving the management and effectiveness of employees' learning
processes within manufacturing companies has attracted a high level of attention in recent …
processes within manufacturing companies has attracted a high level of attention in recent …