Parameter Optimisation of Squeeze Casting Process using LM 20 Alloy: Numeral Analysis by Neural Network and Modified Coefficient-based Deer Hunting Optimization-Reference-Cited by-同舟云学术

Parameter Optimisation of Squeeze Casting Process using LM 20 Alloy: Numeral Analysis by Neural Network and Modified Coefficient-based Deer Hunting Optimization

Published:2020-11-29 Issue: Volume: Page:1-17
ISSN:1448-4846
Container-title:Australian Journal of Mechanical Engineering
language:en
Short-container-title:Australian Journal of Mechanical Engineering

Author:

Panicker Pratheesh G¹,Kuriakose Shajan²

Affiliation:

1. Research Scholar, Department of Mechanical Engineering, Mahatma Gandhi University, Kottayam, Kerala, India

2. HOD in Department of Mechanical Engineering, Mar Athanasius College of Engineering, Kothamangalam, Kerela, India

Publisher

Informa UK Limited

Subject

Mechanical Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/14484846.2020.1842306

Reference30 articles.

1. Evaluation of surface quality and mechanical properties of squeeze casted AA2026 aluminum alloy using response surface methodology

2. Parametric optimization for improving impact strength of squeeze cast of hybrid metal matrix (LM24–SiCp–coconut shell ash) composite

3. On effect of squeezing pressure on microstructural characteristics, heat treatment response and electrical conductivity of an Al-Si-Mg-Ni-Cu alloy

4. Deer Hunting Optimization Algorithm: A New Nature-Inspired Meta-heuristic Paradigm

5. Simulation of transport processes in squeeze casting

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