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Neural network modeling and combined compromise solution (CoCoSo) method for optimization of drilling performances in polymer nanocomposites
Journal of Thermoplastic Composite Materials ( IF 3.6 ) Pub Date : 2020-07-16 , DOI: 10.1177/0892705720939165 Prakhar Kumar Kharwar 1 , Rajesh Kumar Verma 1 , Abhishek Singh 2
Journal of Thermoplastic Composite Materials ( IF 3.6 ) Pub Date : 2020-07-16 , DOI: 10.1177/0892705720939165 Prakhar Kumar Kharwar 1 , Rajesh Kumar Verma 1 , Abhishek Singh 2
Affiliation
Nowadays, polymer nanocomposite becomes a suitable alternative to conventional materials for lightweight and structural applications. Multiwall carbon nanotube (MWCNT)-reinforced epoxy composites p...
中文翻译:
用于优化聚合物纳米复合材料钻孔性能的神经网络建模和组合折衷解 (CoCoSo) 方法
如今,聚合物纳米复合材料已成为用于轻质和结构应用的传统材料的合适替代品。多壁碳纳米管(MWCNT)增强环氧树脂复合材料...
更新日期:2020-07-16
中文翻译:
用于优化聚合物纳米复合材料钻孔性能的神经网络建模和组合折衷解 (CoCoSo) 方法
如今,聚合物纳米复合材料已成为用于轻质和结构应用的传统材料的合适替代品。多壁碳纳米管(MWCNT)增强环氧树脂复合材料...