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Author:Wang, Xiaolei
Title:Artificial Immune Optimization and Its Application in Industrial Electronics
Keinotekoisiin immuunijärjestelmiin perustuva optimointi ja sen sovellus teollisuuselektroniikassa
Publication type:Master's thesis
Publication year:2005
Pages:82      Language:   eng
Department/School:Sähkö- ja tietoliikennetekniikan osasto
Main subject:Tehoelektroniikka   (S-81)
Supervisor:Ovaska, Seppo J.
Instructor:Gao, Xiao-Zhi
OEVS:
Electronic archive copy is available via Aalto Thesis Database.
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Location:P1 Ark S80     | Archive
Keywords:natural immune systems
artificial immune system (AIS)
artificial immune optimization (AIO) methods
clonal selection algorithm (CSA)
genetic algorithms (GA)
function optimization
passive filters
power factor (PF)
biologiset immuunijärjestelmät
keinotekoinen immuunijärjestelmä
keinotekoisiin immuunijärjestelmiin perustuva optimointi
kloonausvalinta-algoritmi
geneettiset algoritmit
funktion optimointi
passiiviset suodattimet
tehokerroin
Abstract (eng): As we know that natural immune systems are complex and enormous self-defence systems with the distinguished capabilities of learning, memory, and adaptation.
Artificial Immune System (AIS), based on the natural immune systems, can be considered as an emerging kind of biologically inspired computational intelligence methods, which have attracted considerable research interest from different communities over the past decade.
Artificial Immune Optimization (AIO) methods are an important partner of the AIS.
They have been successfully applied to handle numerous challenging optimization problems with superior performances over classical approaches.

In this Master's thesis, the essential natural immune principles of circulatory, regulatory, and memory mechanisms are first introduced.
Next, we present a few typical AIS models and algorithms.
In addition, the recent advances of the AIO methods with their applications are discussed.
We also demonstrate the application of the clonal selection algorithm in nonlinear function optimization and LC passive power filter optimal design.
Computer simulations are made to verify its optimization effectiveness.
ED:2005-03-23
INSSI record number: 28189
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