NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
clonal selection based artificial immune system for generalized pattern recognitionThe last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.
Document ID
20150006794
Document Type
Conference Paper
External Source(s)
Authors
Huntsberger, Terry
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Date Acquired
April 27, 2015
Publication Date
October 9, 2011
Subject Category
Numerical Analysis
Cybernetics, Artificial Intelligence and Robotics
Meeting Information
IEEE International Conference on Systems, Man, and Cybernetics (SMC 2011)(Anchorage, AK)
Distribution Limits
Public
Copyright
Other
Keywords
pattern recognition
artificial immune system
classification