A framework for case-based fuzzy multicriteria decision support for tropical cyclone forecasting

Case-based reasoning and multicriteria decision making have common grounds: they are both problem solving methodologies; both involve the selection, ranking and aggregation of best alternatives and provide tools for evaluating the alternatives in respect to multiple attributes or criteria. Each of the two methodologies has its own strengths and weaknesses. By integrating the two methodologies, we can take advantage of their strengths and complement each other´s weaknesses. This paper proposes a multi-stage framework for intelligent decision support that integrates case-based reasoning and fuzzy multicriteria decision making techniques. We illustrated the proposed approach in the context of tropical cyclone prediction. We describe a prototype intelligent decision support system, which helps the forecaster in retrieving best-fitted solutions in terms of both usefulness and similarity to the current observed case.