Smart City Landscape Design Based on Improved Particle Swarm Optimization Algorithm
Joint Authors
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-01
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Aiming at the shortcomings of standard particle swarm optimization (PSO) algorithms that easily fall into local optimum, this paper proposes an optimization algorithm (LTQPSO) that improves quantum behavioral particle swarms.
Aiming at the problem of premature convergence of the particle swarm algorithm, the evolution speed of individual particles and the population dispersion are used to dynamically adjust the inertia weights to make them adaptive and controllable, thereby avoiding premature convergence.
At the same time, the natural selection method is introduced into the traditional position update formula to maintain the diversity of the population, strengthen the global search ability of the LTQPSO algorithm, and accelerate the convergence speed of the algorithm.
The improved LTQPSO algorithm is applied to landscape trail path planning, and the research results prove the effectiveness and feasibility of the algorithm.
American Psychological Association (APA)
Yao, Wenting& Ding, Yongjun. 2020. Smart City Landscape Design Based on Improved Particle Swarm Optimization Algorithm. Complexity،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1143276
Modern Language Association (MLA)
Yao, Wenting& Ding, Yongjun. Smart City Landscape Design Based on Improved Particle Swarm Optimization Algorithm. Complexity No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1143276
American Medical Association (AMA)
Yao, Wenting& Ding, Yongjun. Smart City Landscape Design Based on Improved Particle Swarm Optimization Algorithm. Complexity. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1143276
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143276