Application of rough set theory in geodesic data processing

Sheng Gu; Jiaolong Wei; Jing Guo

doi:10.1117/12.855490

2 April 2010 Application of rough set theory in geodesic data processing

Sheng Gu, Jiaolong Wei, Jing Guo

Proceedings Volume 7651, International Conference on Space Information Technology 2009; 76510Y (2010) https://doi.org/10.1117/12.855490
Event: International Conference on Space Information Technology 2009, 2009, Beijing, China

Abstract

A novel knowledge discovery model, CEDPRS (CE-1 Satellite Data Preprocessing Rough Set), is presented for CE-1 satellite tracking data preprocessing. In order to develop CEDPRS, rough set is chosen as the theoretical tool for its good performance in knowledge discovery, and so are characteristics of the data as well as practical experiences. Then, good diagnosis rules are provided for the discovery and disposal of fault data as a result of CEDPRS applied to tracking data Preprocessing. Experimental results are obtained by introducing real task data, which demonstrate that the proposed CEDPRS model is sufficiently accurate and effective in satellite tracking data preprocessing.

Citation Download Citation

Sheng Gu, Jiaolong Wei, and Jing Guo "Application of rough set theory in geodesic data processing", Proc. SPIE 7651, International Conference on Space Information Technology 2009, 76510Y (2 April 2010); https://doi.org/10.1117/12.855490

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available