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Application areas of AIS: the past, present and future.
Emma Hart,Jon Timmis +1 more
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TLDR
In this paper, the authors take a step back and reflect on the contributions that the Artificial Immune Systems (AIS) has brought to the application areas to which it has been applied, and suggest a set of problem features that they believe will allow the true potential of the immunological system to be exploited in computational systems.Abstract:
After a decade of research into the area of artificial immune systems, it is worthwhile to take a step back and reflect on the contributions that the
paradigm has brought to the application areas to which it has been applied. Undeniably, there have been a lot of successful stories—however, if the
field is to advance in the future and really carve out its own distinctive niche, then it is necessary to be able to illustrate that there are clear benefits to
be obtained by applying this paradigm rather than others. This paper attempts to take stock of the application areas that have been tackled in the
past, and ask the difficult question ‘‘was it worth it ?’’. We then attempt to suggest a set of problem features that we believe will allow the true
potential of the immunological system to be exploited in computational systems, and define a unique niche for AISread more
Citations
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Book ChapterDOI
The dendritic cell algorithm for intrusion detection
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A hybrid immune model for unsupervised structural damage pattern recognition
Bo Chen,Chuanzhi Zang +1 more
TL;DR: The test results show the feasibility of using the hybrid AIPR (HAIPR) method for the unsupervised structural damage pattern recognition, combined with the fuzzy clustering and the artificial immune pattern recognition.
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TL;DR: The results of second case studies show that the proposed method gives better results than two well-known artificial immune systems for real word data sets, and the method is competitive to other classifiers.
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