文章基本信息

标题：Forecasting of zinc coating thickness with artificial neural networks
其他标题：Yapay sinir ağı yaklaşımıyla çinko kalınlığının tahminlenmesi
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作者：Tuğçen Hatipoğlu ; Semra Boran ; Burcu Özcan 等
期刊名称：Sakarya University Journal of Science
印刷版ISSN：1301-4048
电子版ISSN：2147-835X
出版年度：2013
卷号：17
期号：1
语种：English
出版社：Sakarya University
摘要：Since the competition level among the companies is increasing day by day, meeting customer demands with qualified products and cost reduction are primary goals of each company. And zinc, the main raw material in galvanization sector, is the most important cost item. So it is required to forecast the amount of zinc to be spent. In this study it is tried to forecast the amount of zinc consumption using the artificial neural network (ANN) method. To evaluate the convenience of values hypothesis tests are done; and the results showed that there is no significant difference between the predicted and real outputs statistically.
其他摘要：İşletmeler arasında artan rekabet nedeniyle müşterinin istediği kalitede ürün üretmek ve maliyetlerin düşürülmesi öncelikli hedeflerdendir. Galvaniz sektöründe temel hammadde girdisi olan Çinko (Zn), en önemli maliyet kalemini oluşturmaktadır. Hem müşteri
关键词：Forecasting;Metaheuristics;Artificial Neural Networks;Coating Thickness
其他关键词：Tahminleme;Metasezgisel;Yapay Sinir Ağları;Kaplama Kalınlığı