DocumentCode :
3013456
Title :
A New Population Diversity Model in Intelligence Optimization Algorithms
Author :
Feng, Jiqiang ; Xie, Weixin ; Xu, Chen
Author_Institution :
Key Lab. for Intell. Inf. Process., Shenzhen Univ., Shenzhen, China
Volume :
2
fYear :
2009
fDate :
11-14 Dec. 2009
Firstpage :
80
Lastpage :
83
Abstract :
A mathematical framework based on probability theory is presented that enables us to analyze one important aspect of SI algorithms: the population diversity. Firstly the population density degree is defined for the population in the SI algorithms. The population diversity is then discussed from the point of view of the normal distribution in statistics. We show that there is a close connection between the distribution and population diversity and that the essential structure of population diversity is quite similar to that of the distribution. A detailed construction of the population diversity model is then given that is based on probability distributions. The paper concludes with a generic numerical example that validates the population diversity model.
Keywords :
particle swarm optimisation; statistical distributions; SI algorithms; intelligence optimization algorithms; mathematical framework; population density degree; population diversity model; probability distributions; probability theory; swarm intelligence algorithms; Computational intelligence; Security; Normal Distribution; Population Diversity; Probability Theory; Swarm Intelligence;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Security, 2009. CIS '09. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-5411-2
Type :
conf
DOI :
10.1109/CIS.2009.198
Filename :
5375940
Link To Document :
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