A comparative study on modelling material removal rate by ANFIS and polynomial methods in electrical discharge machining process
暂无分享,去创建一个
[1] J. McGeough. Advanced Methods Of Machining , 1988 .
[2] Angelos P. Markopoulos,et al. Artificial neural network models for the prediction of surface roughness in electrical discharge machining , 2008, J. Intell. Manuf..
[3] Mohan Kumar Pradhan,et al. Neuro-fuzzy and neural network-based prediction of various responses in electrical discharge machining of AISI D2 steel , 2010 .
[4] B. Yan,et al. The effect in EDM of a dielectric of a urea solution in water on modifying the surface of titanium , 2005 .
[5] Prasanta Sahoo,et al. Roughness modelling and optimisation in EDM using response surface method for different work piece materials , 2009 .
[6] Jiju Antony,et al. Design of experiments for engineers and scientists , 2003 .
[7] T. L. Kelley,et al. An Unbiased Correlation Ratio Measure. , 1935, Proceedings of the National Academy of Sciences of the United States of America.
[8] C. J. Luis,et al. Material removal rate and electrode wear study on the EDM of silicon carbide , 2005 .
[9] Pedro J. Arrazola,et al. Comparison of the machinabilities of Ti6Al4V and TIMETAL® 54M using uncoated WC–Co tools , 2010 .
[10] Sachin Maheshwari,et al. Some investigations into the electric discharge machining of hardened tool steel using different electrode materials , 2004 .
[11] V. N. Moiseev. Titanium in Russia , 2005 .
[12] David K. Aspinwall,et al. Workpiece surface roughness and integrity after WEDM of Ti–6Al–4V and Inconel 718 using minimum damage generator technology , 2008 .
[13] I. Puertas,et al. Analysis of the influence of EDM parameters on surface quality, MRR and EW of WC–Co , 2004 .
[14] J. S. Khamba,et al. Investigation for ultrasonic machining of titanium and its alloys , 2007 .
[15] Osman Taylan,et al. Neural and fuzzy model performance evaluation of a dynamic production system , 2006 .
[16] Ajay Batish,et al. Electric discharge machining of titanium and its alloys: a review , 2012 .
[17] B. Turkovich,et al. Tool wear in titanium machining , 1982 .
[18] H. Zarepour,et al. Statistical analysis on electrode wear in EDM of tool steel DIN 1.2714 used in forging dies , 2007 .
[19] T. Masuzawa,et al. An index to evaluate the wear resistance of the electrode in micro-EDM , 2004 .
[20] A. Jawaid,et al. The effect of machining on surface integrity of titanium alloy Ti–6% Al–4% V , 2005 .
[21] Rosemar Batista da Silva,et al. Surface integrity of finished turned Ti–6Al–4V alloy with PCD tools using conventional and high pressure coolant supplies , 2007 .
[22] Norliana Mohd Abbas,et al. A review on current research trends in electrical discharge machining (EDM) , 2007 .
[23] Osman Taylan,et al. Determining optimal quality distribution of latex weight using adaptive neuro-fuzzy modeling and control systems , 2011, Comput. Ind. Eng..
[24] R. Purohit,et al. Mathematical modeling of electric discharge machining of cast Al-4Cu-6Si alloy-10wt.% SiCp composites , 2007 .
[25] Pei-Jen Wang,et al. Comparisons of neural network models on material removal rate in electrical discharge machining , 2001 .
[26] Ulaş Çaydaş,et al. Modeling and analysis of electrode wear and white layer thickness in die-sinking EDM process through response surface methodology , 2008 .
[27] T. R. Bement,et al. Taguchi techniques for quality engineering , 1995 .
[28] C. F. Jeff Wu,et al. Experiments: Planning, Analysis, and Parameter Design Optimization , 2000 .
[29] Xiang Li,et al. Regularities in data from factorial experiments , 2006, Complex..
[30] Hamdy A. Taha,et al. Operations Research an Introduction , 2007 .
[31] Pei-Jen Wang,et al. Predictions on surface finish in electrical discharge machining based upon neural network models , 2001 .
[32] Erik Vanhatalo,et al. A Bayesian Analysis of Unreplicated Two-Level Factorials Using Effects Sparsity, Hierarchy, and Heredity , 2011 .
[33] R. Cook. Influential Observations in Linear Regression , 1979 .
[34] Z. M. Wang,et al. Titanium alloys and their machinability—a review , 1997 .
[35] N. Draper,et al. Applied Regression Analysis , 1967 .
[36] Stephen T. Newman,et al. State of the art electrical discharge machining (EDM) , 2003 .
[37] R. K. Bhoi,et al. Artificial Neural Network Prediction of Material Removal Rate in Electro Discharge Machining , 2005 .
[38] David K. Aspinwall,et al. Creep feed grinding of gamma titanium aluminide and burn resistant titanium alloys using SiC abrasive , 2007 .
[39] Osman Taylan,et al. An adaptive neuro-fuzzy model for prediction of student's academic performance , 2009, Comput. Ind. Eng..
[40] J. O. Rawlings,et al. Applied Regression Analysis: A Research Tool , 1988 .
[41] Hisao Ishibuchi,et al. Bidirectional bridge between neural networks and linguistic knowledge: linguistic rule extraction and learning from linguistic rules , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).
[42] C. Daniel. Use of Half-Normal Plots in Interpreting Factorial Two-Level Experiments , 1959 .