The Design And Implementation Of Maize Disease And Pest Diagnosis System Based On Ontology

Most of the current knowledge systems are developed or redeveloped base on the user's different needs, using different knowledge representation methods, different modeling methods and different development tools. Therefore, the interoperability between knowledge systems becomes a problem. not to mention coordinate these systems to solve a problem. Research and applications relate to semantic web and ontology provide corresponding technical basis and practical solutions to deal with the difficulties which are caused by interoperability or knowledge sharing and reuse between distributed knowledge systems. Ontology can give a clear statement of common understanding for a given domain, which will facilitate communication between all the subjects. Reusing and sharing of knowledge in a given domain shall be achieved through these exchanges.In this paper, we studied the construction of ontology-based expert system, which include building Domain Ontology and designing expert system based on domain ontology. This work belongs to the State 863 Project "Digital Agriculture Knowledge Grid Research and Applications". And it is a part of "Web-based Distributed Agricultural Knowledge Consultation Platform".The work in this paper:1. Proposed a method of constructing domain ontology-"Nine-Step"After researching the theoretical knowledge such as the concept of ontology, the main ontology description language, construction methods and development tools, this paper presents a method of constructing domain ontology-"Nine-Step". "Nine-Step" includes the following nine steps:Determine the areas and scope of the ontology; Consider reusing existing ontology; Knowledge acquisition; List terms; Define classes and levels; Defined attributes;Define the side:Define instance:Abnormal test.2. Carried out ontology engineering under the direction of "Nine-Step", built "Maize Disease Diagnosis Ontology" and "Maize Pest Diagnosis Ontology"We manage to represent the domain knowledge of maize disease and pest diagnosis in "Maize Disease Diagnosis Ontology" and "Maize Pest Diagnosis Ontology" through the establishment of the concepts and the relationship between concepts, the definition of instance and constraints over properties. We select OWL DL which is a sublanguage of OWL to describe the ontology. And we chose Protege 3.4.4 which is developed by Stanford University as our ontology development tool.3. Using the ontology model as the knowledge base of maize disease and pest diagnostic system, we carried out the design and implementation of the system by using Visual C# 2008 and Microsoft SQL Server 2005.We worked from the reality of maize pest control, carried out demand analysis and overall design, determined the user, functions and framework of the system. The system uses B/S structure, could be divided into knowledge layer, the data layer, logic layer and the HCI layer in accordance with the functions. System features include the diagnosis of common diseases and pests of maize, the query of the corresponding details of diseases and pest, and the management of diseases and pest. The system can not only diagnose the pests and diseases that have occurred, but also feedback the potential threat of pests to the user; system provides a variety of diagnostic mode, allowing users to choose the right one according to the actual situation.The significance of this work:The "Nine-Step" works well in the scene of building domain ontology by knowledge engineers, and makes ontology maintenance and evolution work much easier. Through the building of "Maize Disease Diagnosis Ontology" and "Maize Pest Diagnosis Ontology", we try to construct a shared, reusable knowledge base for maize disease and pest diagnosis expert system. The ontology-based diagnosis system for maize diseases and pests is not pleasing to the eye and easy to use, but also meet user's demand for information services in agricultural production. All in all, the system has very good practicability.