Using genetic algorithms for improved discrete sequence prediction

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

Abstract

A statistics-based method using genetic algorithms for predicting discrete sequences is presented. The prediction of the next value is based upon a fixed number of previous values and the statistics offered by the training data. According to the statistics, in similar past cases different values occurred next. If these values are considered with the appropriate weights, the forecast is successful. Weights are generated by genetic algorithms.
Original languageEnglish
Title of host publicationProceedings of the International Conference on Artificial Intelligence, IC-AI '03, June 23 - 26, 2003, Las Vegas, Nevada, USA
EditorsHamid R. Arabnia, Rose Joshua, Youngsong Mun
PublisherCSREA
Pages475-481
Number of pages10
Volume1
ISBN (Print)1-932415-12-2
Publication statusPublished - 2003
Event2003 International Conference on Artificial Intelligence - Las Vegas, NV, United States
Duration: 23 Jun 200326 Jun 2003

Conference

Conference2003 International Conference on Artificial Intelligence
Abbreviated titleIC-AI 2003
CountryUnited States
CityLas Vegas, NV
Period23/06/0326/06/03

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Keywords

  • artificial intelligence

Cite this

Ekárt, A. (2003). Using genetic algorithms for improved discrete sequence prediction. In H. R. Arabnia, R. Joshua, & Y. Mun (Eds.), Proceedings of the International Conference on Artificial Intelligence, IC-AI '03, June 23 - 26, 2003, Las Vegas, Nevada, USA (Vol. 1, pp. 475-481). CSREA.