Optimization of nonlinear geological structure mapping using hybrid neuro-genetic techniques
Created by W.Langdon from
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- @Article{Ganesan20112913,
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author = "T. Ganesan and P. Vasant and I. Elamvazuthi",
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title = "Optimization of nonlinear geological structure mapping
using hybrid neuro-genetic techniques",
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journal = "Mathematical and Computer Modelling",
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volume = "54",
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number = "11-12",
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pages = "2913--2922",
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year = "2011",
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ISSN = "0895-7177",
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DOI = "doi:10.1016/j.mcm.2011.07.012",
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URL = "http://www.sciencedirect.com/science/article/pii/S0895717711004225",
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keywords = "genetic algorithms, genetic programming, Nonlinear,
Engineering problems, Geological structure mapping,
Hybrid optimisation",
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abstract = "A fairly reasonable result was obtained for nonlinear
engineering problems using the optimisation techniques
such as neural network, genetic algorithms, and fuzzy
logic independently in the past. Increasingly, hybrid
techniques are being used to solve the nonlinear
problems to obtain a better output. This paper
discusses the use of neuro-genetic hybrid technique to
optimise the geological structure mapping which is
known as seismic survey. It involves minimisation of
objective function subject to the requirement of
geophysical and operational constraints. In this work,
the optimization was initially performed using genetic
programming, and followed by hybrid neuro-genetic
programming approaches. Comparative studies and
analysis were then carried out on the optimised
results. The results indicate that the hybrid
neuro-genetic hybrid technique produced better results
compared to the stand-alone genetic programming
method.",
- }
Genetic Programming entries for
Timothy Ganesan
Pandian Vasant
I Elamvazuthi
Citations