2024-03-29T07:34:36Zhttps://gredos.usal.es/oai/requestoai:gredos.usal.es:10366/1343842024-03-13T09:52:58Zcom_10366_122575com_10366_4512com_10366_3823col_10366_134243
2017-09-05T11:01:44Z
urn:hdl:10366/134384
Isotropic Image Analysis for Improving CBR Forecasting
Mata Conde, Aitor
Muñoz Vicente, María Dolores
Corchado Rodríguez, Emilio Santiago
Corchado Rodríguez, Juan Manuel
Computer Science
A novel hybrid forecasting Case-Based Reasoning (CBR) system is presented in this interdisciplinary study in which an isotropic buffer operator is applied for case-based creation. Commonly used as an image analysis technique by commercial Geographic Information Systems (GIS), the buffer operator in this particular system calculates the area of an oil slick for prediction and visualization tasks. The use of the buffer operator improves the quality of the data used by the system and in consequence the quality of the results obtained. The system generates predictions by using historical data on oil-slick formation following a spill.
2017-09-05T11:01:44Z
2017-09-05T11:01:44Z
2011
info:eu-repo/semantics/article
Journal of Mathematical Imaging and Vision. Volumen 42 (2-3), pp. 212-224. Springer Science + Business Media.
0924-9907(Print)/ 1573-7683(Online)
http://dx.doi.org/10.1007/s10851-011-0315-x
http://hdl.handle.net/10366/134384
en
https://creativecommons.org/licenses/by-nc-nd/3.0/
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivs 3.0 Unported
Springer Science + Business Media