Volume 2, Issue 2

Rough Set Approach to Development of a Knowledge-Based Expert System

Author

B. S. Panda1 *, S. S. Gantayat2 and Ashok Mishra3

Abstract

Abstract:

In this paper we propose to model of a knowledge-based expert systems using the techniques of Rough Sets approach. In the real world problem solving is the process of finding a solution when the path leading to that solution is uncertain. The Expert Systems need to have the ability to handle vague associations, for example by accepting the degree of correlations as numerical certainty factors. When the data is incomplete or missing, the only solution is to accept the value “unknown” and proceed to an approximate reasoning with this missing value. Rough sets provides a framework to model uncertainity, the human way of thinking, reasoning and the perception process. To run an expert system, the engine reasons about the knowledge base like a human. In the 80's a third part appeared: a dialog interface to communicate with users. This ability to conduct a conversation with users was later called "conversational". Rough set theory is a technique deals with uncertainty.

DOI

https://doi.org/10.62226/ijarst20130271

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