دانلود مقاله با موضوع یک رویکرد تشخیص ناهنجاری بر اساس دیفرانسیل هیبریدی تکامل و K-means
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موضوع به انگلیسی:An anomaly detection approach
based on hybrid differential
evolution and K-means clustering
in crowd intelligence
بخشی از متن:Abstract
Purpose – Artificial intelligence is gradually penetrating into human society. In the network era, the
interaction between human and artificial intelligence, even between artificial intelligence, becomes more and
more complex. Therefore, it is necessary to describe and intervene the evolution of crowd intelligence network
dynamically. This paper aims to detect the abnormal agents at the early stage of intelligent evolution.
Design/methodology/approach – In this paper, differential evolution (DE) and K-means clustering are
used to detect the crowd intelligence with abnormal evolutionary trend.
Findings – This study abstracts the evolution process of crowd intelligence into the solution process of DE and use
K-means clustering to identify individualswho are not conducive to evolution in the early stage of intelligent evolution.
Practical implications – Experiments show that the method we proposed are able to find out individual
intelligence without evolutionary trend as early as possible, even in the complex crowd intelligent interactive
environment of practical application. As a result, it can avoid the waste of time and computing resources.
Originality/value – In this paper, DE and K-means clustering are combined to analyze the evolution of
crowd intelligent interaction.
Keywords Differential evolution, K-means, Anomaly detection, Crowd intelligence,
Intelligence evolution
Paper type Research paper
