Abstract—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.

Index Terms—simple random sampling, stratified sampling, systematic sampling, cluster sampling, differential evolution, parameter estimation

Cite: Lu Qingbo, Zhang Xueliang, Wen Shuhua, and Lan Guosheng, "Comparison Four Different Probability Sampling Methods based on Differential Evolution Algorithm," Journal of Advances in Information Technology, Vol. 3, No. 4, pp. 206-214, November, 2012.doi:10.4304/jait.3.4.206-214