Open Access
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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Dissertation
Artificial immune system for static and dynamic production scheduling problems
TL;DR: The findings showed that the hybrid method was proven to give better performance compared to single method in producing optimized solution and reduced solution generating time.
Proceedings ArticleDOI
Association based immune network for multimodal function optimization
Qingzheng Xu,Jing Si,Lei Wang +2 more
TL;DR: The experiments on 10 benchmark functions show that the new algorithm is capable of improving the search performance significantly in global convergence, convergence speed, computational cost, search ability, solution quality and algorithm stability.
Proceedings ArticleDOI
An improved V-detector algorithm of identifying boundary self
TL;DR: The experiment results showed that the new algorithm covers the holes existed in boundary between self region and non-self region more effectively than traditional negative selection algorithm does.
Proceedings ArticleDOI
A Clustering Model Inspired by Humoral Immunity
Yuling Tian,Peng Ren +1 more
TL;DR: Inspired by the relationship of B-cells and antibodies, an effective immune model is presented and the validity of the model is proved through an experiment of motor fault data clustering.
References
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