Author:
Zeydan Mithat,Yazıcı Deniz
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Reference24 articles.
1. Kuo CC, Pietras S (2010) Applying regression analysis to improve dyeing process quality: a case study. Int J Adv Manuf Technol 49:357–368
2. Ravikumar K, Krishnan S, Ramalingam S, Balu K (2006) Optimization of process variables by the application of response surface methodology to optimize the process variables for reactive red and acid brown dye removal using a novel adsorbent. Dyes Pigm 72:66–74
3. Kuo CFJ, Chang CD, Su TL, Fu CT (2008) Optimization of the dyeing process and prediction of quality characteristics on elastic fiber blending fabrics. Polym Plast Technol Eng 47(7):678–687
4. Hench KW, Al-Ghanim AM (1995) The application of a neural network methodology to the analysis of a dyeing operation. In: ANNIE ‘95: artificial neural networks in engineering, St. Louis, MO (United States), pp 873–878
5. Köksal G (1992) Robust design of batch dyeing process. Degree of Doctor of Philosophy, Department of Industrial Engineering, Graduate Faculty of North Carolina State University, Raleigh, NC
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献