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Paper
title

A Particle Swarm Optimization based Neural Network and a Harmony Search Algorithm for Surface Roughness in Face Milling

Credit to Download: 1 | Page Numbers 5 | Abstract Views: 1757
Year: 2009
Present: شفاهي
COI code: ICME10_119
Paper Language: English

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Authors A Particle Swarm Optimization based Neural Network and a Harmony Search Algorithm for Surface Roughness in Face Milling

M. Reza Soleymani - Assistant Professor in Mech. Eng. Dept., Imam Hussein University, Tehran-Iran
  M Asadnia - MSc student in Mech. Eng. Dept., Iran University of Industries and Mines, Tehran-Iran

Abstract:

In this paper, based on the acquired experimental data, the modeling of the face milling operation for surface roughness is performed by using an Improved Particle Swarm Optimization based Neural Network (IPSONN). Then, the Harmony search algorithm (HS) is utilized for optimizing the cutting parameters. The experimental evaluations of the obtained results using the optimal cutting parameters have shown the superiority of the proposed optimization approach.

Keywords:

Harmony search algorithm-Artificial neural network- Particle Swarm Optimization-Cutting parameters Optimization

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COI code: ICME10_119

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Soleymani, M. Reza & M Asadnia, 2009, A Particle Swarm Optimization based Neural Network and a Harmony Search Algorithm for Surface Roughness in Face Milling, 10th Iranian Conference on Manufacturing Engineering (ICME 2010), بابل, دانشگاه صنعتي نوشيرواني بابل, https://www.civilica.com/Paper-ICME10-ICME10_119.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Soleymani, M. Reza & M Asadnia, 2009)
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