Intelligent Agricultural Information System Of Inexact Reasoning And Case-based Reasoning

Knowledge indication methodes and reasoning methodes have been an urgent need aimed for different applying fields because of the development of the expert system theory and the increasing using of the expert system . Uncertainty reasoning and case-based resonning which are methodes used in expert systmes apply in each suitable fields. On the basis of the research on theories of expert system , uncertainty reasoning and case-based resonning(CBR), this paper present two knowledge indication methodes and their corresponding reasoning methods each based on uncertainty reasoning and case-based resonning respectively , these methodes are suitable in agriculture fields .This paper describes a prototype CBR expert system as well.The uncertainty knowledge indication method presented in this paper, based on Production system , make use of fuzzy logic ; and this paper present three formula to caculate the uncertainty degee . There are three types of knowledge in CBR method presented in this paper-case , rule and alias table , and the input is syntactic analysised mainly by the inference engine . The prototype CBR expert system save knowledge in database system , and can be divided into four sections: case retrieval section, case reuse section, case revision section and case retain section. Case retrieval section retrieves the most similar case or cases ;case reuse section reuses the information in that case to solve the problem; case revision section revises the proposed solution and case retain section retaines the parts of the experience likely to be useful for future problem solving .