Paper
31 March 2010 Discovery of emerging patterns with immune network theory
Bo Chen, Chuanzhi Zang
Author Affiliations +
Abstract
This paper presents an immune network-based emergent pattern recognition method. The artificial immune network provides more flexible learning tools than neural networks and clustering technologies. With a neural network, a network structure has to be defined first. The immune network allows their components to change and learn patterns by changing the strength of connections between individual components. The presented computational model achieves emergent pattern recognition by dynamically constructing a network of feature vectors to represent the internal image of input data patterns. The immune network-based emergent pattern recognition approach has tested using a benchmark civil structure. The test result shows the feasibility of using the presented method for the emergent structural damage pattern recognition.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bo Chen and Chuanzhi Zang "Discovery of emerging patterns with immune network theory", Proc. SPIE 7647, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2010, 764727 (31 March 2010); https://doi.org/10.1117/12.847612
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Data modeling

Pattern recognition

Detection and tracking algorithms

Autoregressive models

Cesium

Performance modeling

Neural networks

Back to Top