Scheduled System Maintenance on May 29th, 2015:
IEEE Xplore will be upgraded between 11:00 AM and 10:00 PM EDT. During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

Study on Cost Forecast Method of Power Projects Based on Data Mining Technology

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)
Guangjin Peng ; State Key Lab. of Power Transm. Equip. & Syst. Security & New Technol., Chongqing Univ., Chongqing ; Jihui Yu ; Juntao Wei ; Hui Zhu
more authors

Based on cost data of certain zone history power transmission line projects, applying data mining technology including relative analysis, clustering analysis and support vector machine theory, one kind of new cost forecast methods of power projects is presented. Firstly, applying relative analysis and partial correlation analysis in SPSS15.0 software package, cost forecast index system is built after simplifying technical conditions of power projects. Next, using, clustering analysis, noise information of cost data of history projects is deleted. At last, using support vector machine theory, cost forecast model of power projects is designed. Simulation results of real power transmission line projects in Matlab7.0 software package show such model is valid and feasible.

Published in:

Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on

Date of Conference:

12-14 Oct. 2008