Hybrid Methodology for Structural Health Monitoring Based on Immune Algorithms and Symbolic Time Series Analysis

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ISSN Print: 2150-8402
ISSN Online: 2150-8410
www.scirp.org/journal/jilsa
E-mail: jilsa@scirp.org

"Hybrid Methodology for Structural Health Monitoring Based on Immune Algorithms and Symbolic Time Series Analysis"
written by Rongshuai Li, Akira Mita, Jin Zhou,
published by Journal of Intelligent Learning Systems and Applications, Vol.5 No.1, 2013

has been cited by the following article(s):

[1]	Deterministically generated negative selection algorithm for damage detection in civil engineering systems
	2019

[2]	Time Series Analysis for Vibration-Based Structural Health Monitoring: A Review
	2018

[3]	Numerical simulation and optimization for the vibration of the seed metering device based on a novel ML-IGA method
	2017

[4]	Numerical simulation and optimization for the vibration of the seed metering device based on a novel ML-IGA method.
	Journal of Vibroengineering, 2017

[5]	Inspection and Monitoring of Structural Damage Using Vibration Signatures and Smart Techniques
	Thesis, 2016

[6]	Structural Damage Assessment using an Artificial Immune System
	2015

[7]	Experimental Verification of Parameter Identification Method based on Symbolic Time Series Analysis and Adaptive Immune Clonal Selection Algorithm
	Transactions on Machine Learning and Artificial Intelligence, 2014

[1]	Damage detection in composite beams using negative selection algorithm method Materials Today: Proceedings, 2023 DOI:10.1016/j.matpr.2023.10.108

[2]	Numerical simulation and optimization for the vibration of the seed metering device based on a novel ML-IGA method Journal of Vibroengineering, 2017 DOI:10.21595/jve.2017.17171

[3]	Emerging Design Solutions in Structural Health Monitoring Systems Advances in Civil and Industrial Engineering, 2015 DOI:10.4018/978-1-4666-8490-4.ch005

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