Adaptation of Cases for Case Based Forecasting with Neural Network Support

  • Juan M. Corchado
  • B. Lees


A novel approach to the combination of a case based reasoning system and an artificial neural network is presented in which the neural network is integrated within the case based reasoning cycle so that its generalizing ability may be harnessed to provide improved case adaptation performance. The ensuing hybrid system has been applied to the task of oceanographic forecasting in a real-time environment and has produced very promising results. After presenting classifications of hybrid artificial intelligence problem-solving methods, the particular combination of case based reasoning and neural networks, as a problem-solving strategy, is discussed in greater depth. The hybrid artificial intelligence forecasting model is then explained and the experimental results obtained from trials at sea are outlined.


Artificial Neural Network Bayesian Network Hybrid System Forecast Error Soft Computing 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag London Limited 2001

Authors and Affiliations

  • Juan M. Corchado
  • B. Lees

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