A improved particle swarm optimization based on cloud model with implications for urban land use planning

Yanfei Wei; Yaolin Liu; Dun Wang

doi:10.1117/12.838390

15 October 2009 A improved particle swarm optimization based on cloud model with implications for urban land use planning

Yanfei Wei, Yaolin Liu, Dun Wang

Author Affiliations +

Proceedings Volume 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining; 74923T (2009) https://doi.org/10.1117/12.838390
Event: International Symposium on Spatial Analysis, Spatial-temporal Data Modeling, and Data Mining, 2009, Wuhan, China

Abstract

In order to solve the dependence on the problem of patch technology in the constrained optimization of Particle Swarm Optimization (PSO), conversion will be achieved on the qualitative and quantitative of feasibility rules of the PSO algorithm by the uncertain illation and figure characteristics of cloud .The quantification of binding correction factor will be done in order to realize the common patch methods of different issues. The improved algorithm will be applied to the urban land use planning of Nanning and Yulin city in Guangxi. Quantifying the land conversion factor and combining with spatial analyses technology, analyzing and contrasting the land conversion area of the two cities, this improved algorithm will be proved to settle different problems.

Citation Download Citation

Yanfei Wei, Yaolin Liu, and Dun Wang "A improved particle swarm optimization based on cloud model with implications for urban land use planning", Proc. SPIE 7492, International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining, 74923T (15 October 2009); https://doi.org/10.1117/12.838390

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