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Comparison of Soft Computing Techniques for Modelling of the EDM Performance Parameters
Joint Authors
Cakir, S. H.
Cakir, M. V.
Eyercioglu, O.
Gov, K.
Şahin, Mehmet
Source
Advances in Mechanical Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-06-04
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Selection of appropriate operating conditions is an important attribute to pay attention for in electrical discharge machining (EDM) of steel parts.
The achievement of EDM process is affected by many input parameters; therefore, the computational relations between the output responses and controllable input parameters must be known.
However, the proper selection of these parameters is a complex task and it is generally made with the help of sophisticated numerical models.
This study investigates the capacity of Adaptive Nero-Fuzzy Inference System (ANFIS), genetic expression programming (GEP) and artificial neural networks (ANN) in the prediction of EDM performance parameters.
The datasets used in modelling study were taken from experimental study.
According to the results of estimating the parameters of all models in the comparison in terms of statistical performance is sufficient, but observed that ANFIS model is slightly better than the other models.
American Psychological Association (APA)
Cakir, M. V.& Eyercioglu, O.& Gov, K.& Şahin, Mehmet& Cakir, S. H.. 2013. Comparison of Soft Computing Techniques for Modelling of the EDM Performance Parameters. Advances in Mechanical Engineering،Vol. 2013, no. 2013, pp.1-15.
https://search.emarefa.net/detail/BIM-468538
Modern Language Association (MLA)
Cakir, M. V.…[et al.]. Comparison of Soft Computing Techniques for Modelling of the EDM Performance Parameters. Advances in Mechanical Engineering No. 2013 (2013), pp.1-15.
https://search.emarefa.net/detail/BIM-468538
American Medical Association (AMA)
Cakir, M. V.& Eyercioglu, O.& Gov, K.& Şahin, Mehmet& Cakir, S. H.. Comparison of Soft Computing Techniques for Modelling of the EDM Performance Parameters. Advances in Mechanical Engineering. 2013. Vol. 2013, no. 2013, pp.1-15.
https://search.emarefa.net/detail/BIM-468538
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-468538