Performance Analysis of Source-Linked Harmony Search Algorithm for Big Data Optimization
نویسندگان
چکیده
Bu çalışmada, Harmoni Arama algoritmasının (Harmony Search algorithm, HSA) mevcut veriden faydalanarak başlangıç çözümlerini üretme yaklaşımı ile güçlendirilmiş varyantı olan Kaynak-Bağlantılı (Source-Linked HSA, slinkHSA) performansı elektroensefalografi (EEG) sinyallerinde gürültü minimizasyonu gerektiren büyük veri optimizasyonu üzerinden incelenmiştir. slinkHSA elde edilen sonuçlar diğer meta-sezgisel teknikler tarafından bulunan kıyaslanmıştır. Karşılaştırmalar, harmonilerini EEG sinyalleri kullanılarak üretmenin çözümlerinin kalitesini önemli ölçüde katkıda bulunduğunu ve algoritmanın yakınsama hızını artırdığını göstermiştir.
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ژورنال
عنوان ژورنال: Tbv bilgisayar bilimleri ve mühendisli?i dergisi
سال: 2022
ISSN: ['1305-8991']
DOI: https://doi.org/10.54525/tbbmd.1090787