CNN-DST: Ensemble deep learning based on Dempster–Shafer theory for vibration-based fault recognition
V Yaghoubi, L Cheng… - Structural Health …, 2022 - journals.sagepub.com
Nowadays, using vibration data in conjunction with pattern recognition methods is one of the
most common fault detection strategies for structures. However, their performances depend …
most common fault detection strategies for structures. However, their performances depend …
[HTML][HTML] HOFS: Higher order mutual information approximation for feature selection in R
Feature selection is a process of choosing a subset of relevant features so that the quality of
predictive models can be improved. An extensive body of work exists on information …
predictive models can be improved. An extensive body of work exists on information …
Suri: Feature selection based on unique relevant information for health data
Feature selection, which identifies representative features in observed data, can increase
the utility of health data for predictive diagnosis. Unlike feature extraction, such as PCA and …
the utility of health data for predictive diagnosis. Unlike feature extraction, such as PCA and …
[PDF][PDF] Optimisation method for training deep neural networks in classification of non-functional requirements
M Sabir - 2022 - openresearch.lsbu.ac.uk
Non-functional requirements (NFRs) are regarded critical to a software system's success.
The majority of NFR detection and classification solutions have relied on supervised …
The majority of NFR detection and classification solutions have relied on supervised …