Determining the effect of cutting parameters on surface roughness in hard turning using the Taguchi method I Asiltürk, H Akkuş Measurement 44 (9), 1697-1704, 2011 | 689 | 2011 |
Modeling and prediction of surface roughness in turning operations using artificial neural network and multiple regression method I Asiltürk, M Çunkaş Expert systems with applications 38 (5), 5826-5832, 2011 | 458 | 2011 |
Multi response optimisation of CNC turning parameters via Taguchi method-based response surface analysis I Asiltürk, S Neşeli Measurement 45 (4), 785-794, 2012 | 347 | 2012 |
Optimisation of parameters affecting surface roughness of Co28Cr6Mo medical material during CNC lathe machining by using the Taguchi and RSM methods I Asiltürk, S Neşeli, MA Ince Measurement 78, 120-128, 2016 | 168 | 2016 |
Predicting surface roughness of hardened AISI 1040 based on cutting parameters using neural networks and multiple regression İ Asiltürk The International Journal of Advanced Manufacturing Technology 63, 249-257, 2012 | 59 | 2012 |
Determining the optimum process parameter for grinding operations using robust process S Neşeli, İ Asiltürk, L Celik Journal of mechanical science and technology 26, 3587-3595, 2012 | 46 | 2012 |
Predicting surface roughness of AISI 4140 steel in hard turning process through artificial neural network, fuzzy logic and regression models H Akkuş, I Asilturk Scientific Research and Essays 6 (13), 2729-2736, 2011 | 44 | 2011 |
An intelligent system approach for surface roughness and vibrations prediction in cylindrical grinding İ Asiltürk, M Tinkir, H El Monuayri, L Çelik International Journal of Computer Integrated Manufacturing 25 (8), 750-759, 2012 | 35 | 2012 |
Intelligent adaptive control and monitoring of band sawing using a neural-fuzzy system İ Asiltürk, A Ünüvar journal of materials processing technology 209 (5), 2302-2313, 2009 | 27 | 2009 |
Effects of cutting tool parameters on surface roughness MA Ince, İ Asiltürk Int. J. Eng. Sci 4, 15-22, 2015 | 22 | 2015 |
Application of artificial intelligent to predict surface roughness I Asiltürk Experimental Techniques 38, 54-60, 2014 | 16 | 2014 |
On-line surface roughness recognition system by vibration monitoring in CNC turning using adaptive neuro-fuzzy inference system (ANFIS) I Asilturk International Journal of the Physical Sciences 6 (22), 5353-5360, 2011 | 16 | 2011 |
Prediction of cutting forces and surface roughness using artificial neural network (ANN) and support vector regression (SVR) in turning 4140 steel I Asilturk, H Kahramanli, HE Mounayri Materials Science and Technology 28 (8), 980-986, 2012 | 14 | 2012 |
optimization of fatigue life parameters with Taguchi Method MT Demirci, A Samanchi, N Tarakcioglu, T Asilturk 6th International Advanced Technologies Symposium (IATS’11), 16-18, 2011 | 13 | 2011 |
Testere ile kesme işleminde yapay zeka tabanlı adaptif kontrol uygulaması İ Asiltürk Selçuk Üniversitesi Makina Mühendisliği Anabilim Dalı Doktora Tezi, 2007 | 10 | 2007 |
A Comprehensive Analysis of Surface Roughness, Vibration, and Acoustic Emissions Based on Machine Learning during Hard Turning of AISI 4140 Steel İ Asiltürk, M Kuntoğlu, R Binali, H Akkuş, E Salur Metals 13 (2), 437, 2023 | 9 | 2023 |
Regression modeling of surface roughness in grinding I Asiltürk, L Çelik, E Canli, G Önal Advanced Materials Research 271, 34-39, 2011 | 9 | 2011 |
Mesleki ve teknik eğitimin modernizasyonu projesi ve modüler eğitim sisteminin değerlendirilmesi H Düzcükoğlu, İ Asiltürk, M Yaşar AB Kopenhag Süreci ve Mastriht Bildirgesi Açısından Türkiye’de Mesleki …, 2005 | 9 | 2005 |
Noncontact surface roughness measurement using a vision system E Koçer, E Horozoğlu, I Asiltürk Seventh International Conference on Machine Vision (ICMV 2014) 9445, 432-436, 2015 | 8 | 2015 |
Machinery Monitoring using Vibration Signal Analysis I Asilturk, H Aslanci, U Ozmen International Journal of Mechanical And Production Engineering 5 (2), 21-25, 2017 | 7 | 2017 |