Construction Of Tobacco Disease And Pest Consultation Expert System Based On Network

The tobacco disease and pest consultation expert system was studied with the method of artificial intelligence based on rule reasoning. How to control the disease and pest of tobacco by making use of the expert system that constructed by new information and network technology are major studies area. This system has strong ability for diagnosis and it was designed by ASP.NET and SQL Server 2000. It can perform the expert action and concide to the need of the research and development of tobacco disease. The system possessed five modules: tobacco disease diagnosis, tobacco pest diagnosis, query system for pesticide information, knowledge of disease and pest, system management. Each module was interdependent and isolated operation. Tobacco disease and pest diagnosis module was the kernel part of the system, which was composed of diagnosis for tobacco disease and pest, and provided the control case information. Query system for pesticide, knowledge module and system management were the the auxiliary module, these modules provided the main method of bioassay and toxicology which can supply the theoretical principle for the research; picture management offered many pictures on efficacy trials of pesticide and specimen plants which provided reference data for the further research; system management module that introducted the basic composition, use method, system maintenance and the increase and decrease of the datas was the supplementary module of the system. The system collected many informations and control case for 79 kinds of diseases, 46 pests, 120 pesticides information and 312 pictures were plused. Because kinds of computer technologies (multimedia et al) were used, this system would be provided with a friendlier man-computer interface, a stronger capability, easier operationand quicker query; its knowledge base could also be modified and enlarged. Result in this study showed that it was feasible completely to constructing the expert system for tobacco disease and pest with rule-based reasoning and case-based reasoning technology. In the future the key of the study will be focus on how to improve the low identified rate and how to make the system more easy to be used.