| Autor: |
Ramadhan, Ali J., Abotaleb, Mostafa, Makarovskikh, Tatiana, Mijwil, Maad M. |
| Předmět: |
|
| Zdroj: |
Library of Progress-Library Science, Information Technology & Computer; Jul-Dec2024, Vol. 44 Issue 2s, p1317-1327, 11p |
| Abstrakt: |
GLDMHO is a software algorithm implemented in Python, specifically designed for automatically forecasting univariate time series data using high-order quasilinear recurrence equations. Optimized for large-scale applications, such as temperature datasets, GLDMHO features an automatic model selection system that identifies the optimal order, ranging from first to fifth, to maximize prediction accuracy across diverse datasets. Its dynamic model adjustment capability significantly enhances prediction accuracy and effectively manages fluctuations in various univariate time series data. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
