loading
Documents

Research.Publish.Connect.

Paper

Authors: Nilton Luiz Queiroz Junior ; Luis Gustavo Araujo Rodriguez and Anderson Faustino da Silva

Affiliation: State University of Maringá, Brazil

ISBN: 978-989-758-247-9

Keyword(s): Optimization Selection Problem, Machine Learning, Genetic Algorithms.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence and Decision Support Systems ; Enterprise Information Systems ; Evolutionary Programming ; Problem Solving

Abstract: Artificial Intelligence is a strategy applied in several problems in computer science. One of them is to find good compilers optimizations sequences for programs. Currently, strategies such as Genetic Algorithms and Machine Learning have been used to solve it. This article propose an approach that combines both, Machine Learning and Genetic Algorithms, to solve this problem. The obtained results indicate that the proposed approach achieves performance up to 3.472% over Genetic Algorithms and 4.94% over Machine Learning.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.80.4.76

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Queiroz Junior, N.; Rodriguez, L. and da Silva, A. (2017). Combining Machine Learning with a Genetic Algorithm to Find Good Complier Optimizations Sequences.In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-247-9, pages 397-404. DOI: 10.5220/0006270403970404

@conference{iceis17,
author={Nilton Luiz Queiroz Junior. and Luis Gustavo Araujo Rodriguez. and Anderson Faustino da Silva.},
title={Combining Machine Learning with a Genetic Algorithm to Find Good Complier Optimizations Sequences},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2017},
pages={397-404},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006270403970404},
isbn={978-989-758-247-9},
}

TY - CONF

JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Combining Machine Learning with a Genetic Algorithm to Find Good Complier Optimizations Sequences
SN - 978-989-758-247-9
AU - Queiroz Junior, N.
AU - Rodriguez, L.
AU - da Silva, A.
PY - 2017
SP - 397
EP - 404
DO - 10.5220/0006270403970404

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.