Weather Prediction Using Case-Based Reasoning and Fuzzy Set Theory
Bjarne Hansen, Denis Riordan · 2001
A fuzzy logic based methodology for knowledge acquisition is developed and used for retrieval of temporal cases in a case-based reasoning (CBR) system. The methodology is used to acquire knowledge about what salient features of continuous-vector, unique temporal cases indicate significant similarity between cases. Such knowledge is encoded in a similarity-measuring function and thereby used to retrieve k nearest neighbors (k-nn) from a large database. Predictions for the present case are made from a weighted median of the outcomes of analogous past cases (i.e., the k-nn, or the analog ensemble). Past cases are weighted according to their degree of similarity to the present case.