Cart (Loading....) | Create Account
Close category search window
 

An Improved Particle Swarm Optimization Method Based on Borderline Search Strategy for Transmission Network Expansion Planning

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

4 Author(s)
Dong-xiao Niu ; Sch. of Bus. & Adm., North China Electr. Power Univ., Baoding ; Yun-Peng Ling ; Qi Zhao ; Qing-Ying Zhao

To solve the problem of network expansion, an improved particle swarm optimization algorithm (PSO) is proposed in this paper. This method initialized the particle swarm according to borderline search mind, made the initialized particle near the safety line, overcomes the defect of the uncertainty in the rational distribution of particle initialization, optimizing the range of the initialization. Numerical simulation results of power transmission network planning demonstrate the feasibility and efficiency of this method, and shed new light on the further improving of PSO

Published in:

Machine Learning and Cybernetics, 2006 International Conference on

Date of Conference:

13-16 Aug. 2006

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.