Discovery of emerging patterns with immune network theory
Document Type
Conference Proceeding
Publication Date
6-18-2010
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 SPIE - The International Society for Optical Engineering.
Publication Title
Proceedings of SPIE - The International Society for Optical Engineering
Recommended Citation
Chen, B.,
&
Zang, C.
(2010).
Discovery of emerging patterns with immune network theory.
Proceedings of SPIE - The International Society for Optical Engineering,
7647.
http://doi.org/10.1117/12.847612
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/12143