Evolutionary optimization algorithms and their applications in wireless systems

Nowdays 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 b...

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Main Author: Lu, Shijie
Other Authors: Lu Yilong
Format: Final Year Project
Language:English
Published: 2015
Subjects:
Online Access:http://hdl.handle.net/10356/65752
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-657522023-07-07T17:23:00Z Evolutionary optimization algorithms and their applications in wireless systems Lu, Shijie Lu Yilong School of Electrical and Electronic Engineering Centre for Advanced Information Systems DRNTU::Engineering::Electrical and electronic engineering::Wireless communication systems Nowdays 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. Bachelor of Engineering 2015-12-11T06:02:57Z 2015-12-11T06:02:57Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/65752 en Nanyang Technological University 45 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Wireless communication systems
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Wireless communication systems
Lu, Shijie
Evolutionary optimization algorithms and their applications in wireless systems
description Nowdays 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.
author2 Lu Yilong
author_facet Lu Yilong
Lu, Shijie
format Final Year Project
author Lu, Shijie
author_sort Lu, Shijie
title Evolutionary optimization algorithms and their applications in wireless systems
title_short Evolutionary optimization algorithms and their applications in wireless systems
title_full Evolutionary optimization algorithms and their applications in wireless systems
title_fullStr Evolutionary optimization algorithms and their applications in wireless systems
title_full_unstemmed Evolutionary optimization algorithms and their applications in wireless systems
title_sort evolutionary optimization algorithms and their applications in wireless systems
publishDate 2015
url http://hdl.handle.net/10356/65752
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