Baday, ŞehmusBaşak, HüdayimSönmez, Fikret2019-06-262019-06-262017-10-30Baday, Ş., BaŞak, H., & Sönmez, F. (2017). Küreselleştirme ısıl işlemi uygulanmış AISI 1050 çeliǧinin yüzey pürüzlülük deǧerlerinin yapay sinir aǧları ile modellenmesi. 2017 International Artificial Intelligence and Data Processing Symposium (IDAP), 16-17 September 2017. https://doi.org/10.1109/idap.2017.80903089781538618806https://doi.org/10.1109/idap.2017.8090308https://hdl.handle.net/20.500.12402/2128Estimation of surface roughness values, which is an indication of workpiece quality, is important in terms of reducing the cost and duration of machining. In this study, the surface roughness values of the medium carbon steel subjected to the spheronization heat treatment have estimated by artificial neural networks. ANN network model have been created by being chosen feedforward back propagation network model, the adoption of network structure and learning function LEARNGDM, TRAINLM as training algorithm, MSE for assessment of network performance and two hidden layers. The value of each neuron in the network have been transferred another layer by TANSIG, LOGSIG and PURELIN transfer functions. As a result, the artificial neural networks trained and tested have been found to be easy to use for estimating surface roughness values with a high percentage of R = 0.99001 according to MSE performance.trinfo:eu-repo/semantics/closedAccessAttribution-NonCommercial-ShareAlike 3.0 United StatesYSAYüzey PürüzlülüğüIsıl İşlemANNSurface RoughnessHeat TreatmentConference ObjectN/AN/A