Self-Assembly Quantum Dots Growth Prediction by Quantum-Inspired Linear Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Dias:2011:SQDGPbQLGP,
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title = "Self-Assembly Quantum Dots Growth Prediction by
Quantum-Inspired Linear Genetic Programming",
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author = "Douglas Dias and Anderson Singulani and
Marco Aurelio Pacheco and Patricia Souza and Mauricio Pires and
Omar Vilela Neto",
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pages = "2060--2067",
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booktitle = "Proceedings of the 2011 IEEE Congress on Evolutionary
Computation",
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year = "2011",
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editor = "Alice E. Smith",
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month = "5-8 " # jun,
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address = "New Orleans, USA",
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organization = "IEEE Computational Intelligence Society",
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publisher = "IEEE Press",
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ISBN = "0-7803-8515-2",
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keywords = "genetic algorithms, genetic programming, artificial
neural network, growth parameters database, machine
code programs, quantum dot mean height behaviour,
quantum inspired linear genetic programming, self
assembly quantum dots growth prediction, quantum
computing, quantum dots",
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DOI = "doi:10.1109/CEC.2011.5949871",
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abstract = "In this work we present the application of quantum
inspired linear genetic programming (QILGP) to the
growth of self-assembled quantum dots. Quantum inspired
linear genetic programming is a novel model to evolve
machine code programs exploiting quantum mechanics
principles. Quantum dots are nanostructures that have
been widely applied to optoelectronics devices. The
method proposed here relies on an existing database of
growth parameters with a resulting quantum dot
characteristic to be able to later obtain the growth
parameters needed to reach a specific value for such a
quantum dot characteristic. The computational
techniques were used to associate the growth input
parameters with the mean height of the deposited
quantum dots. Trends of the quantum dot mean height
behaviour as a function of growth parameters were
correctly predicted, improving on the results obtained
by artificial neural network and classical genetic
programming.",
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notes = "CEC2011 sponsored by the IEEE Computational
Intelligence Society, and previously sponsored by the
EPS and the IET.",
- }
Genetic Programming entries for
Douglas Mota Dias
Anderson Pires Singulani
Marco Aurelio Cavalcanti Pacheco
Patricia L Souza
Mauricio P Pires
Omar Paranaiba Vilela Neto
Citations