Design and Development of Application Specific Knowledge_Based Expert System

Abstract

newline In 21st century, expert systems which are application area of Artificial Intelligence newline(AI) become a significant part of our everyday life. New application areas for AI newlineare continuously discovered but expert systems improve the life of those people newlinewho lived in remote area, where experts and their knowledge are not available. newlinePeople entrust their lives to expert systems in the form of various applications newlineused around their environment. Expert system must be developed with enhanced newlineknowledge base which should be rich in knowledge, inference engine with newlineintelligent reasoning drawing ability and user friendly GUI. Nowadays demands newlineof new expert system in rising in every domain but knowledge updating and newlinemaintenance of expert system require human work. So to reduce the human work, newlinesoftware industries develop quality expert system more efficiently, and in a more newlinecost effective way with the new approaches. In the field of AI, the usage of expert newlinesystems is gaining substantial interest due to cost reduction and high quality that it newlinebrings. Development of proposed expert system start by incorporating the new newlinemodules in existing expert systems like Knowledge Management Platform newline(KMP), static and dynamic knowledge base, Dynamic Knowledge Acquisition newlineModule (DKAM). The inference engine is improved with the help of approaches newlinelike fuzzy to enhance the reasoning power of existing expert systems. The main newlineexpected benefits of this approach over traditional approaches are used to make newlineaccurate inferencing of expert systems for horticulture to improve the quantity newlineand production of crops. Empirical studies in industry answer the questions about newlinewhy and when certain approaches are chosen, how these are applied with impact on newlinesingle instances and how to generalize over classes or systems to increase newlineproductivity of high quality expert system.