By Topic

Knowledge-Based Genetic Algorithms and its Application in Multi-Sensor Fusion

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Yuguang Niu ; Coll. of Inf. Eng., Taiyuan Univ. of Technol., Taiyuan ; Gaowei Yan ; Gang Xie ; Zehua Chen
more authors

In this paper, rough set theory (RST) was introduced to discovery knowledge hidden in the evolution process of Genetic Algorithm. Firstly it was used to analyze correlation between individual variables and their fitness function. Secondly, eigenvector was defined to judge the characteristic of the problem. And then the knowledge discovered was used to select evolution subspace and to realize knowledge-based evolution. The result of weight-value optimization of the neural network in multi-sensor information fusion system shows that this method is able to effectively improve the study efficiency and study precision for neural networks.

Published in:

Networked Computing and Advanced Information Management, 2008. NCM '08. Fourth International Conference on  (Volume:1 )

Date of Conference:

2-4 Sept. 2008