Optimization of material removal rate in wire EDM by polynomial neural network models-Reference-Cited by-同舟云学术

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Optimization of material removal rate in wire EDM by polynomial neural network models

Published:2020-05 Issue:2 Volume:36 Page:613-636
ISSN:0824-7935
Container-title:Computational Intelligence
language:en
Short-container-title:Computational Intelligence

Author:

Dutta Prasenjit¹,Majumder Mrinmoy²^ORCID,Panja Subhash Chandra³

Affiliation:

1. Department of Production EngineeringNational Institute of Technology Agartala Tripura India

2. School of Hydroinformatics Engineering (under Civil Engg.)National Institute of Technology Agartala Tripura India

3. Department of Mechanical EngineeringJadavpur University Kolkata West Bengal India

Publisher

Wiley

Subject

Artificial Intelligence,Computational Mathematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/coin.12255

Reference42 articles.

1. Parametric analysis and optimization of wire electrical discharge machining of γ-titanium aluminide alloy

2. Parametric optimisation of wire electrical discharge machining of γ titanium aluminide alloy through an artificial neural network model

3. Semi-empirical model of efficiency of wire electrical discharge machining of hard-to-machine materials

4. Influence of Machine Feed Rate in WEDM of Titanium Ti-6Al-4V with Constant Current (6A) Using Brass Wire

5. Multi-response optimization of process parameters based on response surface methodology for pure titanium using WEDM process

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Polynomial neural network-based group method of data handling algorithm coupled with modified particle swarm optimization to predict permeate flux (%) of rectangular sheet-shaped membrane;Chemical Papers;2021-08-29

2. Modelling and investigating the impact of EDM parameters on surface roughness in EDM of Al/Cu/Ni Alloy;Australian Journal of Mechanical Engineering;2020-07-13

3. Wire EDM process optimization for machining AISI 1045 steel by use of Taguchi method, artificial neural network and analysis of variances;International Journal of System Assurance Engineering and Management;2020-05-20

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