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Эволюционный алгоритм кластеризации

Эволюционный алгоритм кластеризации

Abstract

В статье представлен и исследован новый алгоритм кластеризации, который, в отличие от других известных алгоритмов, позволяет создавать кластеры в режиме on-line, и не требует предварительного определения кластеров. Это дает возможность использования его в динамических интеллектуальных системах для адаптации к меняющейся входной информации.

In this paper new algorithm of clustering is presented and studied. Instead of other known algorithms this algorithm allows creating clusters in on-line mode and doesnt require preliminary determination of clusters. This gives a possibility of using it in dynamic intellectual systems for adaptation to changing input information.

Keywords

ЭВОЛЮЦИОННЫЙ АЛГОРИТМ, КЛАСТЕРИЗАЦИЯ, ЭВОЛЮЦИОННЫЕ СИСТЕМЫ, РЕЖИМ ON-LINE, ИНТЕЛЛЕКТУАЛЬНАЯ ОБРАБОТКА ИНФОРМАЦИИ, НЕЙРОННАЯ СЕТЬ, ОБУЧЕНИЕ

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold