Welcome Guest, you are in: <root> • Login

Page History: Fuzzy set approaches

Compare Page Revisions

27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 Current 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0

« Older Revision - Back to Page History - Newer Revision »

Page Revision: 2010/06/12 13:33

Fuzzy set approaches

• Fuzzy logic uses truth values between 0.0 and 1.0 to represent the degree of membership (such as using fuzzy membership graph)
• Attribute values are converted to fuzzy values
  - e.g., income is mapped into the discrete categories {low, medium, high} with fuzzy values calculated
• For a given new sample, more than one fuzzy value may apply
• Each applicable rule contributes a vote for membership in the categories
• Typically, the truth values for each predicted category are summed
  

Introduce

• 컴퓨터를 인간에 가깝게 하는 일의 어려움
  - 퍼지 이론: 애매함을 처리하는 수리 이론
  

• Fuzzy logic
  “X”가 “A”라는 집합 A(X)에 속하는 정도를 0과 1 사이의 숫자로 표현 예)  _A(X)=0.7
  

• Crisp logic
  - 전체 집합 X를 두 개의 Group, 즉 부분집합 A⊆X에 속하고 있는 요소와 속하고 있지 않는 요소에 이분하는 특성함수(characteristics function)에 의해 정의된다
  

Copyright © 2010 MUST Corp. All rights reserved. must@must.or.kr
This Program is released under the GNU General Public License v2. View the GNU General Public License v2 or visit the GNU website.