Design of adaptive fuzzy model for classification problem

Tzuu Hseng S. Li, Nai Ren Guo, Chao Lin Kuo

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

The main theme of this paper is to set up an adaptive fuzzy model for a new classification problem. At first, we propose a fuzzy classification model that can automatically generate the fuzzy IF-THEN rules by the features of the training database. The consequent part of the fuzzy IF-THEN rule consists of the confident value of the rule and which class the datum should belong to. Then a novel adaptive modification algorithm (AMA) is developed to tune the confident value of the fuzzy classification model. The proposed model comprises three modules, generation of the fuzzy IF-THEN rules, determination of the classification unit, and setup of the AMA. Computer simulations on the well known Wine and Iris databases have tested the performance. Simulations demonstrate that the proposed method can provide sufficiently high classification rate in comparison with other fuzzy classification models.

Original languageEnglish
Pages (from-to)297-306
Number of pages10
JournalEngineering Applications of Artificial Intelligence
Volume18
Issue number3
DOIs
Publication statusPublished - 2005 Apr 1

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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