An adaptive neuro-fuzzy and NSGA-II-based hybrid approach for modelling and multi-objective optimization of WEDM quality characteristics during machining titanium alloy-Reference-Cited by-同舟云学术

An adaptive neuro-fuzzy and NSGA-II-based hybrid approach for modelling and multi-objective optimization of WEDM quality characteristics during machining titanium alloy

Published:2021-07-02 Issue:23 Volume:33 Page:16659-16674
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Goyal Ashish,Gautam Nipun,Pathak Vimal Kumar^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-021-06261-7.pdf

Reference34 articles.

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3. Kanagarajan D, Karthikeyan R, Palanikumar K, Davim JP (2008) Optimization of electrical discharge machining characteristics of WC/Co composites using non-dominated sorting genetic algorithm (NSGA-II). Int J Adv Manuf Technol 36(11–12):1124–1132

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5. Dambatta YS, Sayuti M, Sarhan AA, Ab Shukor HB, Binti Derahman NA, Manladan SM (2019) Prediction of specific grinding forces and surface roughness in machining of AL6061-T6 alloy using ANFIS technique. Ind Lubr Tribol 71:309–317

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