Comparison of Artificial Neural Network and K-Means for Clustering Dairy Cattle
Yazarlar (2)
Hülya Atıl
Ege Üniversitesi, Türkiye
Aslı Akıllı
Kırşehir Ahi Evran Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SCOPUS dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | International Journal of Sustainable Agricultural Management and Informatics | ||
| Dergi ISSN | 2054-5819 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | Scopus | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2016 |
| Cilt / Sayı / Sayfa | 2 / 1 / 40–52 | DOI | 10.1504/IJSAMI.2016.077266 |
| Makale Linki | https://www.inderscience.com/info/inarticle.php?artid=77266 | ||
| Özet |
| Artificial neural network models (ANN's) are machine-learning systems, a type of artificial intelligence. They have been inspired by and developed along the working principles of the human brain and its nerve cells. ANN's are especially used in the modelling of nonlinear systems. With the information learned through repeated experience, similar to human learning, ANN's can provide classification, pattern recognition, optimisation and the realisation of forward-looking forecasts. Artificial neural network studies have been performed in animal husbandry in recent years. They have been used for the prediction of yield characteristics and classification, animal breeding, quality assessment, and disease diagnosis. In this study, classification of dairy cattle using artificial neural networks and cluster analysis are compared. Artificial neural networks models were determined to be more successful than cluster analysis. |
| Anahtar Kelimeler |
| ANN | Artificial neural network | Classification | Dairy cattle |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| SCOPUS | 9 |
| Google Scholar | 18 |