CBR And Its Application In Agriculture Expert System

Case-Based Reasoning is a memory-based method which utilizes old cases and experience to solve new problem, and it can be seen as analogism from a case to another case. Because GBR has much merit such as easily learning and using, facilitated knowledge acquirement, strong adaptability etc, it gets highly regard of artificial intelligence researcher and is an important reasoning technique rising in artifical intelligence field. Its-basic solving steps is divided into five steps: 1) description of new problem; 2) retrieval of cases; 3) adjustment of scheme; 4) evaluate of scheme; 5) learning and maintenance of case.This paper in turn introduces correlative knowledge on case description and a Object Oriented representation, the aim, tenet of casebase organizing and index and a organizing and index method using dynamic clustering, several typical case retrieval methods, the acquirement of adjustment knowledge, the classification of adjustment methods and a transform adjustment model, evaluate method of new case and learning and maintenance of casebase etc.Moreover this paper also stressed discusses two central problem in case retrieval: the setting of property weight and the assignment of local similar degree between property values. For weight setting, first briefly introduces a known weight learning arithmetic based on rough set, and carrying through problem analysis and improvement, also introduces a weight vector gradually learning arithmetic, when user isn't satisfied with current weights, we can use it to revise weights gradually. For local similar degree assignment, we can according to the difference of property types, namely numerical type, disorderly enumeration type and orderly enumeration type, then separately use different method to measure similar degree.Lastly this paper discusses the application of CBR technique in agricultural expert system. Expatiate on material realization of "CBR bean expert system" developed using Delphi 7.0, and experiment analysis on reasoning efficiency and veracity, doing primary explore for the practical application of CBR technique in agricultural field. But also there are some techniques which aren't mature, such as automatization of case adjustment, and further combination of CBR and other techniques, so how to develop out more perfect CBR system is our future research and struggling direction.