Data Clustering on Breast Cancer Data Using Firefly Algorithm with Golden Ratio Method
Küçük Resim Yok
Tarih
2015
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Univ Suceava, Fac Electrical Eng
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Heuristic methods are problem solving methods. In general, they obtain near-optimal solutions, and they do not take the care of provability of this case. The heuristic methods do not guarantee to obtain the optimal results; however, they guarantee to obtain near-optimal solutions in considerable time. In this paper, an application was performed by using firefly algorithm - one of the heuristic methods. The golden ratio was applied to different steps of firefly algorithm and different parameters of firefly algorithm to develop a new algorithm - called Firefly Algorithm with Golden Ratio (FAGR). It was shown that the golden ratio made firefly algorithm be superior to the firefly algorithm without golden ratio. At this aim, the developed algorithm was applied to WBCD database (breast cancer database) to cluster data obtained from breast cancer patients. The highest obtained success rate among all executions is 96% and the highest obtained average success rate in all executions is 94.5%.
Açıklama
Anahtar Kelimeler
artificial Intelligence, heuristic algorithms, clustering algorithms
Kaynak
Advances in Electrical and Computer Engineering
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
15
Sayı
2