Designing Gaussian Membership Functions for Fuzzy Classifier Generated by Heuristic Possibilistic Clustering
Journal: Journal of Information and Organizational Sciences (JIOS) (Vol.37, No. 2)Publication Date: 2013-12-10
Authors : Dmitri A. Viattchenin; Reyhane Tati; Aliaksandr Damaratski;
Page : 127-139
Keywords : fuzzy cluster; fuzzy rule; antecedent; consequent; Gaussian membership function;
Abstract
The paper deals with the problem of constructing Gaussian membership functions of fuzzy sets for fuzzy rules derived from the data by using heuristic algorithms of possibilistic clustering. Basic concepts of the heuristic approach to possibilistic clustering are reminded and the extended technique of constructing membership functions of fuzzy sets is proposed. An illustrative example is given and preliminary conclusions are made.
Other Latest Articles
- Information Technology and Accounting Information Systems’ Quality in Croatian Middle and Large Companies
- Knowledge Organization of Integrated Water Resources Management: A Case of Chi River Basin, Thailand
- Interpretation of Fuzzy Attribute Subsets in Generalized One-Sided Concept Lattices
- The Application of Multimedia Aimed at Improving the Acquisition of Typical Topics in Natural and Social Science Programs in High Schools
- A REVIEW OF ALZHEIMER’S DISEASE FORMATION, DIAG-NOSIS AND TREATMENT
Last modified: 2020-04-21 15:44:01