Development of multi-objective optimization models for electrochemical machining process

By P. Asokan, R. Ravi Kumar, R. Jeyapaul, M. Santhi. 2008

164 citations recorded by the source corpus.

Subfields: Computational Mechanics, Electrical and Electronic Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/a51875b8ae7dad55d1136a6ad4470183fbf4136f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Murali M. Sundaram
2. K. Rajurkar
3. M. Ghasemi Baboly
4. R. Bagherian Azhiri
5. Reza Teimouri
6. Zayd C. Leseman
7. Ajay P. Malshe

In Mechanical Engineering

1. Murali M. Sundaram
2. K. Rajurkar
3. M. Ghasemi Baboly
4. R. Bagherian Azhiri
5. Reza Teimouri
6. Zayd C. Leseman
7. Ajay P. Malshe

Citations in the corpus

• Review of Electrochemical and Electrodischarge Machining (2013, background): “of expert systems currently implemented include artificial neural networks [39-41] and fuzzy logic controls [42, 43].”
• Application of Taguchi, ANFIS and grey relational analysis for studying, modeling and optimization of wire EDM process while using gaseous media (2014, methodology): “This grey system is a useful technique to deal with poor, incomplete and uncertain data [10] that is designated as “Grey” data.”