Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorLu, Shijie
dc.description.abstractNowdays Evolutionary Optimization has recently experienced a remarkable growth. This report convers PSO algorithms and BAT algorithms. Both of them are started with a population which generated randomly and evaluate the population by using the fitness values. However PSO simulates the behaviors of bird flocking, BAT simulates the echolocation of microbats. And using MATLAB software implements the program to compare the two algorithms in Beamforming application. From the result, we can conclude that BAT algorithm is better than PSO algorithm, as BAT algorithm is more efficient and fast. Furthermore, some further improvements, suggestions and recommendation for the similar projects carried on in the future.en_US
dc.format.extent45 p.en_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Wireless communication systemsen_US
dc.titleEvolutionary optimization algorithms and their applications in wireless systemsen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorLu Yilongen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineeringen_US
dc.contributor.researchCentre for Advanced Information Systemsen_US
item.fulltextWith Fulltext-
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
Files in This Item:
File Description SizeFormat 
  Restricted Access
Main Article1.79 MBAdobe PDFView/Open

Page view(s)

Updated on Jul 18, 2024


Updated on Jul 18, 2024

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.