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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
An Immune-Inspired Approach to Anomaly Detection
Jamie Twycross,Uwe Aickelin +1 more
TL;DR: A second generation artificial immune system for process anomaly detection improves on earlier systems by having different artificial cell types that process information, and finds that communication between cells types is key to performance.
Proceedings ArticleDOI
Solving multiobjective clustering using an immune-inspired algorithm
TL;DR: The experimental results on seven artificial data sets with different manifold structure and six real-world data sets show that the NNIA is an effective algorithm for solving multiobjective clustering problems, and the NnIA based multiobjectives clustering technique is a cogent unsupervised learning method.
Proceedings Article
Immune based feature selection for opinion mining
TL;DR: This study used a feature selection technique based on artificial immune system to select the appropriated features for opinion mining and illustrated that the technique has reduced 90% of the features and improved opinion mining accuracy up to 15% with k Nearest Neighbor classifier and up to 6% with Naïve Baiyes classifier.
Proceedings ArticleDOI
The Diagnostic Dendritic Cell Algorithm for robotic systems
TL;DR: This work shows that the D-DCA is capable of successfully diagnosing simple faults within an acceptable time frame, with an acceptable accuracy.
Book ChapterDOI
Optimization of PTA crystallization process based on fuzzy GMDH networks and differential evolutionary algorithm
TL;DR: In this paper, a kind of global real-value optimization algorithm -— ADE algorithm is proposed for optimizing of PTA crystallization process, capable of find the optimal operation conditions effectively and efficiently and suitable for industrial application.
References
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