Research on Coding Technology Based on Semantic for Feature Parameter Optimization

被引：0

作者：

Jin, Ying-hao ^{[1
]}

Sun, Li-quan ^{[2
]}

机构：

[1] Tonghua Normal Univ, Students Affairs Div, Tonghua, Peoples R China

[2] Harbin Univ Sci & Technol, Coll Comp Sci & Technol, Harbin, Peoples R China

来源：

2011 INTERNATIONAL CONFERENCE ON ELECTRONICS, COMMUNICATIONS AND CONTROL (ICECC) | 2011年

关键词：

genetic algorithm; feature parameter optimization; semantic feature modeling; representation of semantic; coding;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

To improve the efficiency of genetic algorithm for feature parameter optimization, a new method is presented. It determines the range of feature parameters by the availability of model, creates the coding structure of individual by model features and coding and decoding individual by features' semantic. This method can not only improve the efficiency of coding and decoding, but also increase the evolution speed of populations. Experiments on computer show that this new method is more adaptable and practicable.

引用

页码：3885 / 3887

页数：3