A new approach for predicting and collaborative evaluating the cutting force in face milling based on gene expression programming
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- @Article{Yang:2013:JNCA,
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author = "Yang Yang and Xinyu Li and Liang Gao and Xinyu Shao",
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title = "A new approach for predicting and collaborative
evaluating the cutting force in face milling based on
gene expression programming",
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journal = "Journal of Network and Computer Applications",
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year = "2013",
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volume = "36",
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number = "6",
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pages = "1540--1550",
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keywords = "genetic algorithms, genetic programming, Cutting force
modelling, Gene expression programming, Face milling,
Collaborative model evaluation",
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ISSN = "1084-8045",
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DOI = "doi:10.1016/j.jnca.2013.02.004",
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URL = "http://www.sciencedirect.com/science/article/pii/S1084804513000428",
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size = "11 pages",
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abstract = "Cutting force is one of the fundamental elements that
can provide valuable insight in the investigation of
cutter breakage, tool wear, machine tool chatter, and
surface finish in face milling. Analysing the
relationship between process factors and cutting force
is helpful to set the process parameters of the future
cutting operation and further improve production
quality and efficiency. Since cutting force is impacted
by the inherent uncertainties in the machining process,
how to predict the cutting force presents a significant
challenge. In the meantime, face milling is a complex
process involving multiple experts with different
domain knowledge, collaborative evaluation of the
cutting force model should be conducted to effectively
evaluate the constructed predictive model. Gene
Expression Programming (GEP) combines the advantages of
the Genetic Algorithm (GA) and Genetic Programming
(GP), and has been successfully applied in function
mining and formula finding. In this paper, a new
approach to predict the face milling cutting force
based on GEP is proposed. At the basis of defining a
GEP environment for the cutting force prediction, an
explicit predictive model has been constructed. To
verify the effectiveness of the proposed approach, a
case study has been conducted. The comparisons between
the proposed approach and some previous works show that
the constructed model fits very well with the
experimental data and can predict the cutting force
with a high accuracy. Moreover, in order to better
apply the constructed predictive models in actual face
milling process, a collaborative model evaluation
method is proposed to provide a distributed environment
for geographical distributed experts to evaluate the
constructed predictive model collaboratively, and four
kinds of collaboration mode are discussed.",
- }
Genetic Programming entries for
Yang Yang
Xinyu Li
Liang Gao
Xinyu Shao
Citations