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31 March 2010Discovery of emerging patterns with immune network theory
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.
Bo Chen andChuanzhi 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
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Bo Chen, 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