Hybrid artificial intelligence methods in oceanographic forecast models
Fecha de publicación
Institute of Electrical & Electronics Engineers (IEEE)
IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews). Volumen 32 (4), pp. 307-313. Institute of Electrical & Electronics Engineers (IEEE).
An approach to hybrid artificial intelligence problem solving is presented in which the aim is to forecast, in real time, the physical parameter values of a complex and dynamic environment: the ocean. In situations in which the rules that determine a system are unknown or fuzzy, the prediction of the parameter values that determine the characteristic behavior of the system can be a problematic task. In such a situation, it has been found that a hybrid artificial intelligence model can provide a more effective means of performing such predictions than either connectionist or symbolic techniques used separately. The hybrid forecasting system that has been developed consists of a case-based reasoning system integrated with a radial basis function artificial neural network. The results obtained from experiments in which the system operated in real time in the oceanographic environment, are presented
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