Enhanced prediction and optimization of WEDM for titanium alloy (grade 5) with hybrid artificial neural network based meta-heuristics
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s12008-024-02058-9.pdf
Reference52 articles.
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3. Sharma, N., Khanna, R., Gupta, R.: Multi quality characteristics of WEDM process parameters with RSM. Proced. Eng. 64, 710–719 (2013). https://doi.org/10.1016/j.proeng.2013.09.146
4. Kumar, A., Kumar, V., Kumar, J.: Investigation of machining characterization for wire wear ratio & MRR on pure titanium in WEDM process through response surface methodology. J. Process Mech. Eng. 232(1), 108–126 (2018). https://doi.org/10.1177/0954408916685588
5. Chaudhary, T., Siddiquee, A.N., Chanda, A.K.: Effect of wire tension on different output responses during wire electric discharge machining on AISI 304 stainless steel. Def. Technol. 15, 541–544 (2019). https://doi.org/10.1016/j.dt.2018.11.003
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