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https://doi.org/10.17559/TV-20170303013036

Improved Fruit Fly Optimization Algorithm-based density peak clustering and its applications

Ruihong Zhou ; School of Management, Jilin University, School of Management Science and Information Engineering, Jilin University of Finance and Economics, 3699 Jingyue Street, Changchun 130117, China
Qiaoming Liu ; School of Computer Science and Engineering, Changchun University of Technology, 2055 Yanan Street, Changchun 130012, China
Zhengliang Xu ; School of Management, Jilin University, 2699 Qianjin Street, Changchun 130012, China
Limin Wang ; School of Management Science and Information Engineering, Jilin University of Finance and Economics, 3699 Jingyue Street, Changchun 130117, China
Xuming Han ; School of Computer Science and Engineering, Changchun University of Technology, 2055 Yanan Street, Changchun 130012, China


Puni tekst: hrvatski pdf 638 Kb

str. 473-480

preuzimanja: 352

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Puni tekst: engleski pdf 638 Kb

str. 473-480

preuzimanja: 619

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Sažetak

As density-based algorithm, Density Peak Clustering (DPC) algorithm has superiority of clustering by finding the density peaks. But the cut-off distance and clustering centres had to be set at random, which would influence clustering outcomes. Fruit flies find the best food by local searching and global searching. The food found was the parameter extreme value calculated by Fruit Fly Optimization Algorithm (FOA). Based on the rapid search and fast convergence superiorities of FOA, it is possible to make up the casualness of DPC. An improved fruit fly optimization-based density peak clustering algorithm was proposed as FOA-DPC. The FOA-DPC algorithm would be more efficient and effective than DPC algorithm. The results of seven simulation experiments in UCI data sets validated that the proposed algorithm did not only have better clustering performance, but also were closer to the true clustering numbers. Furthermore, FOA-DPC was applied to practical financial data analysis and the conclusion was also effective.

Ključne riječi

clustering centres; cut-off distance; Density Peak Clustering (DPC); Fruit Fly Optimization

Hrčak ID:

179858

URI

https://hrcak.srce.hr/179858

Datum izdavanja:

14.4.2017.

Podaci na drugim jezicima: hrvatski

Posjeta: 1.810 *