TY  - GEN 
AU  - Ruiz Aguilar, Juan Jesús
AU  - Moscoso López, José Antonio
AU  - Urda Muñoz, Daniel
AU  - González Enrique, Francisco Javier
AU  - Turias Domínguez, Ignacio J.
PY  - 2020
UR  - http://hdl.handle.net/10259/7250
AB  - An accurate prediction of freight volume at the sanitary facilities of seaports is a key factor
to improve planning operations and resource allocation. This study proposes a hybrid approach
to forecast container volume at the sanitary facilities of...
LA  - eng
PB  - MDPI
KW  - Maritime transport
KW  - Container forecasting
KW  - Support vector regression
KW  - Self-organizing maps
KW  - Machine learning
KW  - Hybrid models
KW  - Informática
KW  - Computer science
TI  - A Clustering-Based Hybrid Support Vector Regression Model to Predict Container Volume at Seaport Sanitary Facilities
DO  - 10.3390/app10238326
VL  - 10
ER  -