On the evolution of ellipsoidal recognition regions in Artificial Immune Systems
作者： Seral Ozsen , Cuneyt Yucelbas
DOI: 10.1016/J.ASOC.2015.03.014
关键词: Orientation (computer vision) 、 Mutation (genetic algorithm) 、 Detector 、 Artificial immune system 、 Artificial intelligence 、 Clonal selection 、 Ellipsoid 、 Genetic algorithm 、 Pattern recognition 、 Computer science
摘要: In the mutation procedure of this study, an Ab can go through any three kinds (center, length and orientation mutation). An Artificial Immune System was developed based on ellipsoidal recognition regions.Clonal selection principle utilizes for generating best regions.Different applied speed algorithm.Applications were done some benchmark data real-world datasets taken from UCI machine learning repository.Good promising results have been obtained. Using different shapes regions in Systems (AIS) are not a new issue. Especially, seem to be more intriguing as they also used very effectively other shape space-based classification methods. Some studies AIS detectors but restricted their detector scheme - Genetic Algorithms (GA). with by inspiring clonal effective search applied. Performance evaluation tests conducted well application problems repository Comparison GA these problems. Very comparatively good ratios recorded.
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