Feature subset selection in structural health monitoring data using an advanced binary slime mould algorithm
Author:
Affiliation:
1. Structural Dynamics and Assessment Laboratory, School of Civil Engineering, University College Dublin, Dublin, Ireland
Funder
Science Foundation Ireland
Publisher
Informa UK Limited
Subject
Mechanical Engineering,General Materials Science,Building and Construction,Civil and Structural Engineering
Link
https://www.tandfonline.com/doi/pdf/10.1080/24705314.2023.2230398
Reference61 articles.
1. An efficient binary slime mould algorithm integrated with a novel attacking-feeding strategy for feature selection
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3. Deep Learning-Based Crack Identification for Steel Pipelines by Extracting Features from 3D Shadow Modeling
4. A review of vibration-based damage detection in civil structures: From traditional methods to Machine Learning and Deep Learning applications
5. An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection
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