RT Conference Proceedings
T1 Hybridization and optimization of machine learning techniques for improved forecasting in real-world scenarios
A1 Stoean, Ruxandra
K1 Optimización matemática
AB Different and powerful machine learning paradigms are constantly in a race for delivering the lowest error and/or the highest comprehensibility. But what can certainly lead to better forecasting is model inter-cooperation or intra-optimization. The aim of the current talk is to put forward some recent ideas for such hybridization and optimization. Demonstrative experiments are outlined for problems coming from real, challenging environments.
YR 2017
FD 2017-02-14
LK http://hdl.handle.net/10630/13070
UL http://hdl.handle.net/10630/13070
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026