Bazı ülkelerin Endüstri 4.0 düzeylerinin makine öğrenmesi kümeleme algoritmalarıyla belirlenmesi
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Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Artvin Çoruh Üniversitesi
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Yapay zeka teknolojisinin desteklemiş olduğu Endüstri 4.0 ile ülkeler, endüstriyel alanda verimliliği arttırarak, iş akış süreçlerini hızlandırarak ve maliyeti düşürerek üretim gücünü arttırmayı hedeflemektedir. Endüstri 4.0 ve yapay zeka ile gelen yenilikler her ne kadar endüstriyel bazda bir gelişme olarak değerlendirilse de, insan hayatını her alanda etkileyen uygulamalar ile öne çıkmaktadır. Bu çalışmada Endüstri 4.0 ve yapay zeka bileşenleri açıklanarak, 54 ülke ve Endüstri 4.0 etkilerinin görülebileceği alanlardaki 22 değişkenden oluşan verilerle Python programlama dili ile Makine Öğrenmesi yöntemi kullanılmış ve toplanan veriler içerisinden gerekli veri temizleme işlemi yapılmıştır. Ayrıca, 54 ülke, kümeleme yöntemlerinden Hiyerarşik kümeleme yöntemi ve K-Ortalama kümeleme yöntemi kullanılarak elde edilen kümeler birbirleriyle kıyaslanmıştır. Anahtar Kelimeler: Endüstri 4.0, Yapay Zeka, Python Programlama Dili, Hiyerarşik Kümeleme, K-Ortalama Kümeleme Yöntemi.
With Industry 4.0, supported by artificial intelligence technology, countries aim to increase production power by increasing productivity in the industrial field, speeding up work flow processes and reducing costs. Although the innovations that come with Industry 4.0 and artificial intelligence are considered as developments, they stand out with applications that affect human life in all areas. For this reason, in this study, by explaining Industry 4.0 and artificial intelligence components, the Python programming language and Machine Learning method were used with the data consisting of 54 countries and 22 variables in the areas where the effects of Industry 4.0 can be seen, and the necessary data cleaning process was carried out from the collected data. In addition, "the hierarchical clustering method" and "the K-Mean clustering method", which are among the 54 country clustering methods,. Clusters obtained by both hierarchical and K-means clustering methods were compared with each other. Country-based variable rates were evaluated. Keyword; Industry 4.0, Artificial Intelligence, Python, Hierarchical Clustering, KMeans Clustering
With Industry 4.0, supported by artificial intelligence technology, countries aim to increase production power by increasing productivity in the industrial field, speeding up work flow processes and reducing costs. Although the innovations that come with Industry 4.0 and artificial intelligence are considered as developments, they stand out with applications that affect human life in all areas. For this reason, in this study, by explaining Industry 4.0 and artificial intelligence components, the Python programming language and Machine Learning method were used with the data consisting of 54 countries and 22 variables in the areas where the effects of Industry 4.0 can be seen, and the necessary data cleaning process was carried out from the collected data. In addition, "the hierarchical clustering method" and "the K-Mean clustering method", which are among the 54 country clustering methods,. Clusters obtained by both hierarchical and K-means clustering methods were compared with each other. Country-based variable rates were evaluated. Keyword; Industry 4.0, Artificial Intelligence, Python, Hierarchical Clustering, KMeans Clustering
Açıklama
Lisansüstü Eğitim Enstitüsü, İşletme Ana Bilim Dalı
Anahtar Kelimeler
İşletme, Business Administration
