2024-03-29T14:00:56Zhttps://gredos.usal.es/oai/requestoai:gredos.usal.es:10366/1345042024-03-13T10:03:10Zcom_10366_122575com_10366_4512com_10366_3823col_10366_134486
2017-09-06T09:05:05Z
urn:hdl:10366/134504
Neuro-symbolic Reasoning System for Modeling Complex Behaviours.
Corchado RodrÃguez, Juan Manuel
Aiken, Jim
Rees, Nigel
Computer Science
A neuro-symbolic reasoning strategy for modelling a complex system is presented in which the aim is to forecast, in real time, the physical parameter values of a dynamic environment: the ocean. In situations in which the rules that determine a system are unknown the prediction of the parameter values that determine the characteristic behaviour of the system can be a problematic task. In such a situation it has been found that a case-based reasoning system, in combination with an artifical neural network, can provide a more effective means of performing such predictions than other connectionist or symbolic techniques. The case-based reasoning system incorporates a radial basis function artificial neural network for the case adaptation. The results obtained from experiments, in which the system operated in real time in the oceanographic environment, are presented.
2017-09-06T09:05:05Z
2017-09-06T09:05:05Z
2003
info:eu-repo/semantics/article
Innovation in knowledge Engineering.
0-9751004-0-8
http://hdl.handle.net/10366/134504
en
info:eu-repo/semantics/openAccess
Advanced Knowledge International, Australia