- author = "Jung-Jib Kim and Byoung-Tak Zhang",
- title = "Effects of Selection Schemes in Genetic Programming for Time Series Prediction",
- booktitle = "Proceedings of the Congress on Evolutionary Computation",
- year = "1999",
- editor = "Peter J. Angeline and Zbyszek Michalewicz and Marc Schoenauer and Xin Yao and Ali Zalzala",
- volume = "1",
- pages = "252--258",
- address = "Mayflower Hotel, Washington D.C., USA",
- publisher_address = "445 Hoes Lane, P.O. Box 1331, Piscataway, NJ 08855-1331, USA",
- month = "6-9 " # jul,
- organisation = "Congress on Evolutionary Computation, IEEE / Neural Networks Council, Evolutionary Programming Society, Galesia, IEE",
- publisher = "IEEE Press",
- keywords = "genetic algorithms, genetic programming, time series, breeder genetic algorithm, dynamics control, evolutionary algorithms, evolutionary computation, hard selection, laser time-series data, performance testing, selection differential, selection operators, selection schemes, soft selection, time series prediction, variable-size representations, variable-size tree representation, evolutionary computation",
- ISBN = "0-7803-5536-9 (softbound)",
- ISBN = "0-7803-5537-7 (Microfiche)",
-
URL = "
http://bi.snu.ac.kr/Publications/Conferences/International/CEC99_Kim.pdf",
-
DOI = "
10.1109/CEC.1999.781933",
- size = "7 pages",
- abstract = "The problem of time series prediction provides a practical benchmark for testing the performance of evolutionary algorithms. In this paper, we compare various selection methods for genetic programming, an evolutionary computation with variable-size tree representations, with application to time series data. Selection is an important operator that controls the dynamics of evolutionary computation. A number of selection operators have been so far proposed and tested in evolutionary algorithms with fixed-size chromosomes. However, the effect of selection schemes remains relatively unexplored in evolutionary algorithms with variable-size representations. We analyse the evolutionary dynamics of genetic programming by means of the selection to response and the selection differential proposed in the breeder genetic algorithm (BGA). The empirical analysis using the laser time-series data suggests that hard selection is more preferable than soft selection. This seems due to the lack of heritability in genetic programming",
-
notes = "CEC-99 - A joint meeting of the IEEE, Evolutionary
Programming Society, Galesia, and the IEE.
Library of Congress Number = 99-61143
A Study on Effects of Selection Schemes in Genetic Programming for Time Series Prediction, Jung-Jib Kim, Master Thesis, Dept. of Computer Engineering, Seoul National University, February 2000",
