Theoretic and Application Research of Geo-Case Based Reasoning
地理案例推理及其应

As an emerging branch of AI, Case-Based Reasoning (CBR) has the inborn ability of quantitative interpretation and prediction simply based on similarity of historical events even there is difficulty to get the working mechanism, principles, or build statistical models for those complex systems. Since it is a perfect model of human recognition and its working mechanism is very similar to the human primitive reasoning logic, the introduction of CBR to geographical system (Geo-case Based Reasoning) study to solve the problem of quantitative prediction was promoted. With tracking the front of international CBR research, expression and reasoning models of CBR have been promoted. And application of CBR model and method to specific geographical phenomenon has been fully discussed as well. The content of this paper can be summarized in the following aspects: (1) GeoCBR has been posed from the view of geographic case study. Furthermore, principle difference between GeoCBR and general CBR has been explored. (2) A comprehensive expression model for geographic case based reasoning has been established based on Tesseral model. (3) Geo-case based reasoning model was built in case of having fuzzy spatial-temporal distribution, a special FMP was used to calculate similarity of Geo-cases, and then reasoning model was given based on it. (4) With such a theoretical framework of Geo-CBR, a fishing ground prediction model, which can be regarded as a sample of Geo-CBR, has been built. This model has been applied to the East China Sea fishing center prediction. The validation result is satisfying.