Abstract: Case based reasoning (CBR) is a kind of reasoning technology in the field of artificial intelligence in recent years. Feature selection is the hot topic and the difficulty in CBR technology. In order to get optimal feature subset in feature selection process, this paper combines gray correlation degree analysis with genetic algorithm (GA), taking the gray correlation analysis result as the initial population for GA heuristic search, and proposes a new GA-CBR case reasoning optimization model. The test results show this model is effective to improve the CBR forecast accuracy.


Key words: case based reasoning, genetic algorithm, feature selection, gray correlation analysis, optimization