Research On Ontology-based Intelligent Diagnosis System Of Tea Pests

Ontology, which is a concept modeling tool in semantic and knowledge hierarchy description, has been paid much more attention since it was proposed. Ontology has been broadly applied in knowledge engineering, digital library, software reuse, information retrieval, web heterogeneity processing and semantic web. This paper introduces Ontology into the field of tea, construct tea pests Ontology based on the background of knowledge in domain of tea. The constructed Ontology, which has clarity and unique definition of tea pests concepts, is used as semantic tool in tea pests diagnosis system and promote a well communication between persons and machines.This paper mainly focuses on two key problems in intelligent tea pests diagnosis system -- conceptual modeling and intelligent diagnosis reasoning of tea pests diagnosis ontology. Theories and methods of ontology modeling for tea pests are proposed and an ontology-based intelligent tea pests diagnosis prototype system is developed respectively in this paper.The main contents of research and achievement in this paper can be abstracted as followings:1. A tea pests-oriented theories and methods of concepts modeling based on Ontology Web Language (OWL) are researched in this paper. A knowledge representation of tea pests based on ontology is proposed and realized by OWL. Meanwhile, the ontology-based tea pests diagnosis concepts modeling and detecting on the property of consistency of ontology are presented.2. A tea pests-oriented theory and method of building intelligent diagnosis reasoning models based on ontology is proposed in this paper. Through analyzing the characteristics from the domain of tea pests, a retrieval and diagnosis strategy of tea pests is realized by using a method combining with description logic and semantic inference.3. An intelligent diagnosis prototype system of tea pests ontology is developed on Eclipse platform, which adopts Jsp / Servlet programming technology. The correctness of theories and methods are validated through experiments.The research achievements in this paper is not only helpful for effective expressing, organization, management, reusing and sharing of plant pests, but also have significances on both theory and practice in enhancing the capability of plant pests diagnostic system on ability of problem solving and collaborative, increasing the intelligence level of plant pests diagnostic system, and further researching on the agricultural knowledge engineering theory and key technologies.