Authors: Arun Solanki; Ela Kumar
Addresses: School of ICT, Gautam Buddha University, R.N. 209, Greater Noida, U.P., India ' School of ICT, Gautam Buddha University, Greater Noida, U.P., India
Abstract: This paper reports a new approach for providing intelligence in the expert system for diagnosis of diseases for rose flower. It describes the development of a web-based intelligent disease diagnosis system. This expert system is based on a fuzzy logic approach and the Euclidean distance method. This approach is based on rule advancement strategy. This approach enables the drawing of inferences with the enhanced intelligence. This approach is used in the existing fuzzy technique for inferencing in expert system. The proposed expert system incorporates new features: 1) development of knowledge management platform; 2) dynamic knowledge base creation strategy. The dynamically prompted rules are derived from those diagnosis sessions which resulted in successful decisions. This enables more efficient decision-making in the future sessions; 3) dynamic knowledge acquisition; 4) explanation facility which incorporates the rule firing history and rule explanation generator. This expert system gives an acceptable diagnosis of diseases. The inferences are drawn faster compared to traditional approaches. The proposed expert system which is based on rule advancement strategy has been tested for flower rose.
Keywords: expert systems; dynamic knowledge base; rule advancement strategy; RAS; fuzzy logic; PHP; knowledge management platform; KMP; roses; rose diseases; flower diseases; flowers; web-based diagnosis; intelligent diagnosis; disease diagnosis; Euclidean distance; knowledge acquisition; rule firing history; rule explanation generator.
International Journal of Intelligent Systems Design and Computing, 2017 Vol.1 No.1/2, pp.3 - 27
Received: 31 Oct 2013
Accepted: 24 Jan 2014
Published online: 10 Mar 2017 *