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.
|Title of host publication||Proceedings of the International Conference on Artificial Intelligence, IC-AI '03, June 23 - 26, 2003, Las Vegas, Nevada, USA|
|Editors||Hamid R. Arabnia, Rose Joshua, Youngsong Mun|
|Number of pages||10|
|Publication status||Published - 2003|
|Event||2003 International Conference on Artificial Intelligence - Las Vegas, NV, United States|
Duration: 23 Jun 2003 → 26 Jun 2003
|Conference||2003 International Conference on Artificial Intelligence|
|Abbreviated title||IC-AI 2003|
|City||Las Vegas, NV|
|Period||23/06/03 → 26/06/03|
- artificial intelligence
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.