DocumentCode
2341958
Title
New Method of Judging Sub-Health State Based on Rough Sets and BP Neural Network
Author
Liu Bin ; Luo Sen-lin ; Pan Li-min ; Liu Yun-jie ; Ye Ming-de ; Zhang Tie-mei
Author_Institution
Lab. for Inf. Security & Countermeasures, Beijing Inst. of Technol., Beijing, China
fYear
2010
fDate
23-25 April 2010
Firstpage
1
Lastpage
4
Abstract
We propose a new decision model for sub-health in this paper. Unlike traditional statistical analysis method, the model is built with rough sets and BP neural network with 18743 items of data owning 155 dimensions of attributes, we divide sub-health state into three different grade at first in order to reflect the precision of the model. The results of experiments show that the precision of judgment is 94.4% for male test data set and 96.53% for female. Besides these, the feedback strategy helps to improve the performance of the model.
Keywords
backpropagation; bioinformatics; feedback; neural nets; rough set theory; statistical analysis; BP neural network; decision model; feedback strategy; rough sets; statistical analysis method; subhealth state; Biochemistry; Data preprocessing; Diseases; Eyes; History; Neural networks; Neurofeedback; Psychology; Rough sets; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering and Computer Science (ICBECS), 2010 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-5315-3
Type
conf
DOI
10.1109/ICBECS.2010.5462524
Filename
5462524
Link To Document