Self-Assembly Quantum Dots Growth Prediction by Quantum-Inspired Linear Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{Dias:2011:SQDGPbQLGP,

• title = "Self-Assembly Quantum Dots Growth Prediction by Quantum-Inspired Linear Genetic Programming",
• author = "Douglas Dias and Anderson Singulani and Marco Aurelio Pacheco and Patricia Souza and Mauricio Pires and Omar Vilela Neto",
• pages = "2060--2067",
• booktitle = "Proceedings of the 2011 IEEE Congress on Evolutionary Computation",
• year = "2011",
• editor = "Alice E. Smith",
• month = "5-8 " # jun,
• address = "New Orleans, USA",
• organization = "IEEE Computational Intelligence Society",
• publisher = "IEEE Press",
• ISBN = "0-7803-8515-2",
• 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",
• DOI = "doi:10.1109/CEC.2011.5949871",
• 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.",
• 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