Optimization of Multi-Objective Coverage Strategy Based on Multiple Particle Swarm Coevolutionary Algorithm for Water Environment Monitoring System

This paper built a multi-objective optimization model and proposed an improved multi-objective particle swarm optimization algorithm called MPS2O ,which is based on Multiple Particle Swarm Co-evolutionary. The MPS2O algorithm has considerable potential for solving multi-objective optimization proble...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Applied Mechanics and Materials Ročník 742; číslo Sensors, Mechatronics and Automation II; s. 360 - 363
Hlavní autoři: Tian, Li Wei, Zhao, Hong Wei
Médium: Journal Article
Jazyk:angličtina
Vydáno: Zurich Trans Tech Publications Ltd 01.03.2015
Témata:
ISBN:3038354236, 9783038354239
ISSN:1660-9336, 1662-7482, 1662-7482
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:This paper built a multi-objective optimization model and proposed an improved multi-objective particle swarm optimization algorithm called MPS2O ,which is based on Multiple Particle Swarm Co-evolutionary. The MPS2O algorithm has considerable potential for solving multi-objective optimization problems. Mathematical benchmark functions also shows that the proposed algorithm is an excellent Alternative for solving multi-objective optimization problems. Making full use of the research findings home and abroad, MPS2O has been chosen to be the coverage optimization strategy of the wireless sensor networks in Water Environment Monitoring System. Simulation results demonstrate that the MPS2O algorithm is more efficient than the PSO algorithm in solving this real-world problem.
Bibliografie:Selected, peer reviewed papers from the 2014 2nd International Conference on Sensors, Mechatronics and Automation (ICSMA 2014), December 28-29, 2014 Shenzhen, China
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISBN:3038354236
9783038354239
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.742.360