Comparing Predictability of Genetic Programming and ANFIS on Drilling Performance Modeling for GFRP Composites
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @Article{Abhishek:2014:PMS,
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author = "Kumar Abhishek and Biranchi Narayan Panda and
Saurav Datta and Siba Sankar Mahapatra",
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title = "Comparing Predictability of Genetic Programming and
{ANFIS} on Drilling Performance Modeling for {GFRP}
Composites",
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journal = "Procedia Materials Science",
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volume = "6",
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pages = "544--550",
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year = "2014",
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note = "3rd International Conference on Materials Processing
and Characterisation (ICMPC 2014)",
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ISSN = "2211-8128",
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DOI = "doi:10.1016/j.mspro.2014.07.069",
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URL = "http://www.sciencedirect.com/science/article/pii/S2211812814004349",
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abstract = "Drilling of glass fibre reinforced polymer (GFRP)
composite material is substantially complicated from
the metallic materials due to its high structural
stiffness (of the composite) and low thermal
conductivity of plastics. During drilling of GFRP
composites, problems generally arise like fibre pull
out, delamination, stress concentration, swelling,
burr, splintering and micro cracking etc. which reduces
overall machining performance. Now-a-days hybrid
approaches have been received remarkable attention in
order to model machining process behaviour and to
optimise machining performance towards subsequent
improvement of both quality and productivity,
simultaneously. In the present research, spindle speed,
feed rate, plate thickness and drill bit diameter have
been considered as input parameters; and the machining
yield characteristics have been considered in terms of
thrust and surface roughness (output responses) of the
drilled composite product. The study illustrates the
applicability of genetic programming with the help of
GPTIPS as well as Adaptive Neuro Fuzzy Inference System
(ANFIS) towards generating prediction models for better
understanding of the process behavior and for improving
process performances in drilling of GFRP composites.",
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keywords = "genetic algorithms, genetic programming, Glass fibre
reinforced polymer (GFRP), Adaptive Neuro Fuzzy
Inference System (ANFIS), GPTIPS.",
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notes = "PhD thesis (2015) http://ethesis.nitrkl.ac.in/6916/
Experimental Investigations on Machining of CFRP
Composites: Study of Parametric Influence and Machining
Performance Optimization. PhD thesis. does not seem to
be on GP",
- }
Genetic Programming entries for
Kumar Abhishek
Biranchi Narayan Panda
Saurav Datta
Siba Sankar Mahapatra
Citations