Dynamic Knowledge Acquisition Process of online Fuzzy Disease Diagnosis Expert System for Home Pets

This Paper reports a design and development of web based Fuzzy Expert System in specific domain. In Fuzzy Inferencing technique Most Probable and Least Probable Symptoms is considered to drawing the conclusion. Euclidean Distance method is used to calculate accurate result and reliability for the diagnosis result. This Expert System contains two types of database; Static Database and Dynamic Database. Static Knowledge Base will contain all the information of symptoms and disease of Home pets like Dog, Cat etc. Static database contains the data and heuristic knowledge about the specific domain, which gathers the data about the domain, was accomplished by Knowledge Engineer, these data is encoded in to Knowledge Base and Expert System is developed in a particular domain. The drawback of this system is, once knowledge base is developed it is become difficult to update the knowledge base without intervention of programmer. To deal this difficulty Dynamic Acquisition module will be facilitated to up to date Knowledge Base. Knowledge Base contains the textual as well as pictorial information of disease and symptoms, which can help to better understanding about the System. Using these techniques Fuzzy Expert System is implemented in Veterinary Domain.