Automatic Generation of Fuzzy Rules for Fuzzy Databases Using Particle Swarm Optimization

This paper focuses on building a rule based model for a fuzzy database using particle swarm optimization and fuzzy clustering. Traditional databases handle data, which is crisp, deterministic and precise in nature. However our reasoning and decision-making process is uncertain and vague in nature. This paper gives an insight into the world of uncertainty. Using fuzzy rules techniques to enhance this decision making process. The proposed methodology, involves of building a fuzzy set rules on top of a relational database to automatically generate series of fuzzy tables.