- author = "Heitor S. Lopes and Wagner R. Weinert",
- title = "EGIPSYS: an Enhanced Gene Expression Programming Approach for Symbolic Regression Problems",
- journal = "International Journal of Applied Mathematics and Computer Science",
- year = "2004",
- volume = "14",
- number = "3",
- pages = "375--384",
- month = sep,
- note = "Special Issue: Evolutionary Computation",
- keywords = "genetic algorithms, genetic programming, gene expression programming, evolutionary computation, symbolic regression, mathematical modeling, systems identification",
- ISSN = "1641-876X",
-
URL = "
https://www.amcs.uz.zgora.pl/?action=paper&paper=208",
-
URL = "
https://www.amcs.uz.zgora.pl/?action=download&pdf=AMCS_2004_14_3_7.pdf",
- size = "10 pages",
- abstract = "This enhanced system, called EGIPSYS, has features specially suited to deal with symbolic regression problems. Amongst the new features implemented in EGIPSYS are: new selection methods, chromosomes of variable length, a new approach to manipulating constants, new genetic operators and an adaptable fitness function. All the proposed improvements were tested separately, and proved to be advantageous over the basic GEP. EGIPSYS was also applied to four difficult identification problems and its performance was compared with a traditional implementation of genetic programming (LilGP). Overall, EGIPSYS was able to obtain consistently better results than the system using genetic programming, finding less complex solutions with less computational effort. The success obtained suggests the adaptation and extension of the system to other classes of problems.",
-
notes = "AMCS University of Zielona Gora Press
Centro Federal de Educacao Tecnologica do Parana / CPGEI Av. 7 de setembro, 3165, 80230-901 Curitiba (PR), Brazil
March 2014 amc1434.pdf appears to be a different paper",
