A Comparison of Methods to Construct an Optimal Membership Function in a Fuzzy Database System

A fuzzy set is one in which membership in a category is not Boolean, rather items have a degree of membership. Fuzzy databases expand on this idea by storing fuzzy data and allowing data to be retrieved based on its degree of membership. Determining the degree of membership that satisfies the largest number of users is difficult. Five different methods of determining the membership function: the Direct Rating Method, the Random Method with step sizes of .02 and .03, the Steplock Method, and the Weighted Average Method, were compared on the basis of convergence and user satisfaction. The results support use of the Direct Rating Method and the Steplock Method in conjunction with each other, to produce the membership function in the least time and with the highest user satisfaction.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Year dc:date.available

2006

Author dc:creator

• Cunningham, Joanne Marie

Contributors dc:contributor

• Dr. Lorraine Parker

• defuzzification
• weighted average method
• linguistic modifer
• database
• fuzzy logic
• Computer Sciences
• Physical Sciences and Mathematics

Statement dc:rights

• © The Author

Identifier

https://scholarscompass.vcu.edu/etd/877

OAI identifier oai:identifier

oai:scholarscompass.vcu.edu:etd-1876