Using genetic algorithms for improved discrete sequence prediction

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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.

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Publication date2003
Publication titleProceedings 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
Original languageEnglish
Event2003 International Conference on Artificial Intelligence - Las Vegas, NV, United States

Conference

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

    Keywords

  • artificial intelligence

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