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Developing a diagnostic system through integration of fuzzy case-based reasoning and fuzzy ant colony system Expert Systems with Applications 28(2005). Author: R.J. Kuo, Y.P. Kuo, Kai-Ying Chen Speaker: Chih-Yao Chien. Outline. Introduction CBR Fuzzy CBR ACS ASCA

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Author r j kuo y p kuo kai ying chen speaker chih yao chien

Developing a diagnostic system through integration of fuzzy case-based reasoning and fuzzy ant colony systemExpert Systems with Applications 28(2005)

Author: R.J. Kuo, Y.P. Kuo,

Kai-Ying Chen

Speaker: Chih-Yao Chien


Outline
Outline case-based reasoning and fuzzy ant colony system

  • Introduction

  • CBR

    • Fuzzy CBR

  • ACS

    • ASCA

    • Fuzzy ant K-means algorithm

  • Experiment

  • Q&A


Introduction
Introduction case-based reasoning and fuzzy ant colony system

  • In order to cope with huge amount of data and information in the business, varieties of methods including artificial intelligence and statistical methods are developed to extract valuable information from the raw data.

  • Case-based reasoning is one of these methods.


Case based reasoning cbr
Case-based reasoning (CBR) case-based reasoning and fuzzy ant colony system

  • CBR - Searching for similar cases from the historical cases for user as consulting references in solving needed problems.

  • CBR cycle: retrieve, reuse, revise, retain.


Case based reasoning cbr1
Case-based reasoning (CBR) case-based reasoning and fuzzy ant colony system

  • Fuzzy CBR – fuzzy sets theory is used for evaluating similarity between a new case and the existing cases in the case base.

  • In general CBR matching mechanism, successful matching of a selected index is an all-or-nothing affair.the interval may be too small or specific resulting in no matches for a given observed feature set.requiring a very large case library to cover the input space.


Case based reasoning cbr2
Case-based reasoning (CBR) case-based reasoning and fuzzy ant colony system

  • Fuzzy similarity method is proposed to improve the effectiveness of indexing and matching accuracy.


Ant colony system acs
Ant colony system (ACS) case-based reasoning and fuzzy ant colony system


Ant colony system acs asca
Ant colony system (ACS)-ASCA case-based reasoning and fuzzy ant colony system

  • Fuzzy ant system-based clustering algorithm


Ant colony system acs fuzzy ak
Ant colony system (ACS)-Fuzzy AK case-based reasoning and fuzzy ant colony system

  • Fuzzy ant K-means algorithm


Experiment
Experiment case-based reasoning and fuzzy ant colony system


Experiment1
Experiment case-based reasoning and fuzzy ant colony system


Experiment2
Experiment case-based reasoning and fuzzy ant colony system

  • Fuzzy sets theory indeed improves the ASCA+AK method.

  • This study has presented the capability advantages of using fuzzy CBR.

    • Thinking style of human beings.

    • Easily extract the domain knowledge experts’ know-how.

    • Searching time is considerably less.


Experiment3
Experiment case-based reasoning and fuzzy ant colony system

  • Drawbacks

    • Find sufficient amount of cases.

    • Most domain experts are not willing to provide their own know-how.

    • If there are too many selections for a single attribute, it is possible that these selections are extremely close.


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