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Comparison Four Different Probability Sampling Methods based on Differential Evolution Algorithm
Author(s) -
LU Qing-bo,
Xueliang Zhang,
Wen Shu-hua,
Guosheng Lan
Publication year - 2012
Publication title -
journal of advances in information technology
Language(s) - English
Resource type - Journals
ISSN - 1798-2340
DOI - 10.4304/jait.3.4.206-214
Subject(s) - algorithm , sampling (signal processing) , computer science , mathematics , statistics , computer vision , filter (signal processing)
Differential Evolution (DE) is one kind of evolution algorithm, which based on difference of individuals. DE has exhibited good performance on optimization problem. The current studies almost are based on the simple random sampling method, and so this paper investigates other probability sampling methods, and proposed three novel differential evolution algorithms. The proposed algorithms are compared with the original differential evolution algorithm. The numerical results and Lorenz parameter estimation problem show that the new methods performed better than the original differential evolution algorithm

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