MAKİNE ÖĞRENME METOTLARININ MANTI KALİTESİNİN BELİRLENMESİNDE KULLANILABİLİRLİĞİ
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PDF downloads: 4
Keywords:
CIE Lab Sistemi, Decision Tree, Gıda İşleme, Gıda Kalitesi, Makine Öğrenmesi, Mantı VerisetiAbstract
Geleneksel gıdalardan biri olan ve sevilerek tüketilen mantının, endüstriyel üretimdeki çeşitli
süreçlerde karşılaşılabilecek sorunlar nedeniyle kalitesi düşebilmektedir. Kalite kontrolde kullanılan CIE
Lab sistemi yani üç nokta yöntemi olarak da bilinen renk sistemine göre mantı üretiminde ürünün kalite
düşüşleri belirlenebilmektedir. Bu çalışmada mantı üretiminde ısıl işlem süresine göre oluşturulan mantı
veriseti (Mikrodalga seviyesi, L, a, b ve zaman) bazı Makine Öğrenmesi (MÖ) yöntemleri kullanılarak
işlenmiştir. Bu işlem sonucunda ise en yüksek f-score’un 87% ile DT (Decision Tree) sınıflandırıcısı ile
elde edildiği, bu sonucun ise 73% ile Linear çekirdek kullanılan SVM (Support Vector Machine) ve 71%
ile N_neighbours çekirdeği kullanan K-NN (K-Nearest Neighbor) tarafından takip edildiği görülmüştür.
Sonuç olarak, MÖ yöntemleri kullanılarak mantı üretim süreçlerinde ürün kalitesi ve güvenilirliğinin
arttırılabileceği görülmüştür.
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