Multi-performance Optimization in End Milling of GFRP Composites Using Backpropagation Neural Network and Differential Evolution Algorithm
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-0867-5_39
Reference10 articles.
1. PrasanthISNVR, Ravishankar DV, Hussain MM, Badiganti CM, Sharma VK, Pathak S (2018) Investigations on performance characteristics of GFRP composites in milling. Int J Adv Manuf Technol 99(5):1351–1360
2. AzmiAI, Lin RJT, Bhattacharyya D (2013) Machinability study of glass fibre-reinforced polymer composites during end milling. Int J Adv Manuf Technol 64(1):247–261
3. PrashanthISNVR, Ravi Shankar DV, Manzoor Hussain M, Chandra Mouli B (2018) Critical analysis in milling of GFRP composites by various end mill tools. Mater Today: Proc 5(6):14607–14617, (Part 2)
4. SaikumarS, Shunmugam MS (2006) Parameter selection based on surface finish in high-speed end-milling using differential evolution. Mater Manuf Process 21(4):341–347
5. YildizAR (2013) A new hybrid differential evolution algorithm for the selection of optimal machining parameters in milling operations. Appl Soft Comput 13(3):1561–1566
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