Experimental Determination of Cutting Forces and Surface Roughness when Turning 50CrV4 Steel (SAE 6150) and Modelling with the Artificial Neural Network Approach

Hasan Basri Ulas

doi:10.1007/s12666-014-0410-y

Experimental Determination of Cutting Forces and Surface Roughness when Turning 50CrV4 Steel (SAE 6150) and Modelling with the Artificial Neural Network Approach

Transactions of the Indian Institute of Metals ◽

10.1007/s12666-014-0410-y ◽

2014 ◽

Vol 67 (6) ◽

pp. 869-879 ◽

Cited By ~ 4

Author(s):

Hasan Basri Ulas

Keyword(s):

Neural Network ◽

Surface Roughness ◽

Artificial Neural Network ◽

Experimental Determination ◽

Cutting Forces ◽

Network Approach ◽

Neural Network Approach ◽

Artificial Neural ◽

Artificial Neural Network Approach

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An artificial neural network approach to investigate surface roughness and vibration of workpiece in boring of AISI1040 steels

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-015-7621-1 ◽

2015 ◽

Vol 83 (5-8) ◽

pp. 919-927 ◽

Cited By ~ 7

Author(s):

K. Venkata Rao ◽

K. P. Vidhu ◽

T. Anup Kumar ◽

N. Narayana Rao ◽

P. B. G. S. N. Murthy ◽

...

Keyword(s):

Neural Network ◽

Surface Roughness ◽

Artificial Neural Network ◽

Network Approach ◽

Neural Network Approach ◽

Artificial Neural ◽

Artificial Neural Network Approach

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An artificial neural network approach to predict energy consumption and surface roughness of a natural material

SN Applied Sciences ◽

10.1007/s42452-020-2987-6 ◽

2020 ◽

Vol 2 (7) ◽

Author(s):

Mohammad Arafat ◽

Teddy Sjafrizal ◽

Rino Andias Anugraha

Keyword(s):

Neural Network ◽

Surface Roughness ◽

Artificial Neural Network ◽

Energy Consumption ◽

Natural Material ◽

Network Approach ◽

Neural Network Approach ◽

Artificial Neural ◽

Artificial Neural Network Approach

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Surface roughness modeling in high speed turning of Ti-6Al-4V – Artificial Neural Network approach

Materials Today Proceedings ◽

10.1016/j.matpr.2017.07.099 ◽

2017 ◽

Vol 4 (8) ◽

pp. 7654-7664 ◽

Cited By ~ 1

Author(s):

Grynal D'Mello ◽

P. Srinivasa Pai ◽

Rashmi P. Shetty

Keyword(s):

Neural Network ◽

Surface Roughness ◽

Artificial Neural Network ◽

High Speed ◽

Network Approach ◽

Neural Network Approach ◽

High Speed Turning ◽

Artificial Neural ◽

Artificial Neural Network Approach

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A hybrid Taguchi-artificial neural network approach to predict surface roughness during electric discharge machining of titanium alloys

Journal of Mechanical Science and Technology ◽

10.1007/s12206-014-0637-x ◽

2014 ◽

Vol 28 (7) ◽

pp. 2831-2844 ◽

Cited By ~ 43

Author(s):

Sanjeev Kumar ◽

Ajay Batish ◽

Rupinder Singh ◽

T. P. Singh

Keyword(s):

Neural Network ◽

Surface Roughness ◽

Artificial Neural Network ◽

Titanium Alloys ◽

Electric Discharge ◽

Network Approach ◽

Electric Discharge Machining ◽

Neural Network Approach ◽

Artificial Neural ◽

Artificial Neural Network Approach

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Studies on Effect of Cutting Parameters on Surface Roughness of Al-Cu-TiC MMCs: An Artificial Neural Network Approach

Procedia Computer Science ◽

10.1016/j.procs.2015.03.145 ◽

2015 ◽

Vol 45 ◽

pp. 745-752 ◽

Cited By ~ 10

Author(s):

Biswajit Das ◽

Susmita Roy ◽

R.N. Rai ◽

S.C. Saha

Keyword(s):

Neural Network ◽

Surface Roughness ◽

Artificial Neural Network ◽

Cutting Parameters ◽

Network Approach ◽

Neural Network Approach ◽

Artificial Neural ◽

Artificial Neural Network Approach

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An asymmetric flow injection determination of hydroquinone and catechol: An analytic hierarchy and artificial neural network approach

Measurement ◽

10.1016/j.measurement.2019.03.025 ◽

2019 ◽

Vol 139 ◽

pp. 454-466 ◽

Cited By ~ 1

Author(s):

Samira Boroumand ◽

Mansour Arab Chamjangali ◽

Ghadamali Bagherian

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Flow Injection ◽

Network Approach ◽

Asymmetric Flow ◽

Analytic Hierarchy ◽

Neural Network Approach ◽

Artificial Neural ◽

Artificial Neural Network Approach

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A review on the artificial neural network approach to analysis and prediction of seismic damage in infrastructure

International Journal of Hydromechatronics ◽

10.1504/ijhm.2019.104386 ◽

2019 ◽

Vol 2 (4) ◽

pp. 178 ◽

Cited By ~ 15

Author(s):

Manouchehr Shokri ◽

Kian Tavakoli

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Seismic Damage ◽

Network Approach ◽

Neural Network Approach ◽

Artificial Neural ◽

Artificial Neural Network Approach

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Understanding and predicting the dissemination of scientific papers on social media: a two-step simultaneous equation modeling–artificial neural network approach

Scientometrics ◽

10.1007/s11192-021-04051-5 ◽

2021 ◽

Author(s):

Yaxue Ma ◽

Zhichao Ba ◽

Yuxiang Zhao ◽

Jin Mao ◽

Gang Li

Keyword(s):

Neural Network ◽

Social Media ◽

Artificial Neural Network ◽

Simultaneous Equation ◽

Equation Modeling ◽

Network Approach ◽

Neural Network Approach ◽

Scientific Papers ◽

Artificial Neural ◽

Artificial Neural Network Approach

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Accurate determination of natural gas compressibility factor by measuring temperature, pressure and Joule-Thomson coefficient: Artificial neural network approach

Journal of Petroleum Science and Engineering ◽

10.1016/j.petrol.2021.108427 ◽

2021 ◽

pp. 108427

Author(s):

Mahmood Farzaneh-Gord ◽

Hamid Reza Rahbari ◽

Behnam Mohseni-Gharesafa ◽

Alexander Toikka ◽

Irina Zvereva

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Accurate Determination ◽

Compressibility Factor ◽

Network Approach ◽

Neural Network Approach ◽

Thomson Coefficient ◽

Gas Compressibility ◽

Artificial Neural Network Approach

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Efficacy evaluation of oxide-MWCNT water hybrid nanofluids: An experimental and artificial neural network approach

Colloids and Surfaces A Physicochemical and Engineering Aspects ◽

10.1016/j.colsurfa.2021.126562 ◽

2021 ◽

Vol 620 ◽

pp. 126562

Author(s):

Vikas Kumar ◽

Ashutosh Pare ◽

Arun Kumar Tiwari ◽

Subrata Kumar Ghosh

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Network Approach ◽

Efficacy Evaluation ◽

Neural Network Approach ◽

Hybrid Nanofluids ◽

Artificial Neural ◽

Artificial Neural Network Approach

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