Genetic Ink Drop Spread

被引：5

作者：

Sagha, Hesam ^{[1
]}

Shouraki, Saeed Bagheri ^{[2
]}

Beigy, Haimid ^{[1
]}

Khasteh, Hosein ^{[1
]}

Enayati, Elham ^{[3
]}

机构：

[1] Sharif Univ Technol Tehran, Dept Comp Engn, Tehran, Iran

[2] Sharif Univ Technol Tehran, Dept Elect Engn, Tehran, Iran

[3] Brijand Univ Med Sci, Brijand, Iran

来源：

2008 INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, VOL II, PROCEEDINGS | 2008年

关键词：

active learning method; genetic-fuzzy system; ink drop spread;

D O I：

10.1109/IITA.2008.588

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper describes a genetic-fuzzy system adapted to find efficient partitions on data domains for IDS (Ink Drop Spread). IDS is the engine of Active Learning Method (ALM), a methodology of soft computing. IDS extracts useful information from a system subjected to modeling. Proposed method, called GIDS (Genetic IDS), uses genetic algorithm which optimizes the parameters of membership functions that represent the partitions on data planes. Obtained Results showed that using genetic algorithm to find the partitions has better accuracy than the previous generic IDS methods.

引用

页码：603 / +

页数：2

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