Adaptive Splines and Genetic Algorithms

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

An adaptive genetic spline (AGS) technique was proposed for fitting adaptive splines via adjusted generalized cross-validation (GCV) and genetic search. The AGS program was designed to determine the model from the space S m,t which minimizes an adjusted GCV criterion. Simulations were used to examine the performance of AGS. AGS was set to fit cubic splines with a maximum of 400 generations and a crossover probability of 0.8. It was shown that AGS performed well, due to the directed global selection of basis functions.

Original languageEnglish (US)
Title of host publicationProceedings of the Fifth Joint Conference on Information Sciences, JCIS 2000, Volume 1
EditorsP.P. Wang, P.P. Wang
Pages547-550
Number of pages4
Edition1
StatePublished - 2000
EventProceedings of the Fifth Joint Conference on Information Sciences, JCIS 2000 - Atlantic City, NJ, United States
Duration: Feb 27 2000Mar 3 2000

Publication series

NameProceedings of the Joint Conference on Information Sciences
Number1
Volume5

Conference

ConferenceProceedings of the Fifth Joint Conference on Information Sciences, JCIS 2000
CountryUnited States
CityAtlantic City, NJ
Period2/27/003/3/00

ASJC Scopus subject areas

  • Computer Science(all)

Fingerprint Dive into the research topics of 'Adaptive Splines and Genetic Algorithms'. Together they form a unique fingerprint.

Cite this