Development of energy consumption model of abrasive machining process by a combined evolutionary computing approach
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @Article{Vijayaraghavan:2015:Measurement,
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author = "R. Vijayaraghavan and A. Garg and
V. Vijayaraghavan and Liang Gao",
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title = "Development of energy consumption model of abrasive
machining process by a combined evolutionary computing
approach",
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journal = "Measurement",
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volume = "75",
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pages = "171--179",
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year = "2015",
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ISSN = "0263-2241",
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DOI = "doi:10.1016/j.measurement.2015.07.055",
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URL = "http://www.sciencedirect.com/science/article/pii/S0263224115004066",
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abstract = "Abrasive machining is employed for improving surface
characteristics of components used in oil and gas
applications. Optimization of power consumed in
abrasive machining process is vital from environmental
standpoint that requires the formulation of the
generalized and an explicit mathematical model. In the
present work, we propose to study the power consumption
in abrasive machining process using a combined
evolutionary computing approach based on Multi-Adaptive
Regression Splines (MARS) and Genetic Programming (GP)
techniques. Sensitivity and parametric analysis have
also been conducted to capture the dynamics of process
by unveiling dominant input variables and hidden
non-linear relationships. It is concluded that
selection of optimal machining time and abrasive is
necessary for achieving better environmental
performance of abrasive machining process.",
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keywords = "genetic algorithms, genetic programming, Abrasive
machining, MARS, Energy consumption, Modelling",
- }
Genetic Programming entries for
R Vijayaraghavan
Akhil Garg
Venkatesh Vijayaraghavan
Liang Gao
Citations