Performance Evaluation of Fuzzy based Ontology System for Identification of Malaria Disease

The disease identification from the symptoms and other detail is one of the important research area for researcher. The various ontology systems which relate the symptom and disease is evaluated by the researchers. Many time this system fail due to confusing symptom which make the fuzzy problem for classification. In this paper fuzzy based ontology system is presented. The fuzziness of the symptoms is solving by generating and optimizing the rule base. The Malaria disease has been used to evaluate the performance of classifier. The accuracy of classification on symptoms database is the key parameter used for performance evaluation of method.