FSfRT: Forecasting System for Red Tides

A hybrid neuro-symbolic problem-solving model is presented in which the aim is to forecast parameters of a complex and dynamic environment in an unsupervised way. 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 hybrid case-based reasoning system can provide a more effective means of performing such predictions than other connectionist or symbolic techniques. The system employs a case-based reasoning model to wrap a growing cell structures network, a radial basis function network and a set of Sugeno fuzzy models to provide an accurate prediction. Each of these techniques is used at a different stage of the reasoning cycle of the case-based reasoning system to retrieve historical data, to adapt it to the present problem and to review the proposed solution. This system has been used to predict the re...

• Type: Journal
• Year: 2004
• Where: APIN
• Authors: Florentino Fdez-Riverola, Juan M. Corchado
• Keywords: APIN 2004, Case-based Reasoning, Case-based Reasoning Model, Hybrid Case-based Reasoning