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提出一种多目标强度Pareto 混沌差分进化算法(SPCDE). 首先利用Tent 映射进行种群的混沌初始化, 采用一种基于均匀排挤机制的截断排挤操作和混沌替换操作进行种群的环境选择操作; 然后基于一种变缩放因子的差分变异策略进行变异操作, 通过计算支配关系得到变异个体; 最后通过支配关系的计算和环境选择操作进行进化选择操作并得到子代个体. 以上操作不仅提高了算法的收敛性能, 而且保证了Paret...
基于Pareto 解集关联与预测的动态多目标进化算法
动态多目标进化算法 Pareto 解集关联与预测 超块
2014/9/23
针对动态多目标优化问题, 提出一种基于Pareto 解集关联与预测的动态多目标进化算法(LP-DMOEA), 设计了基于超块的Pareto 解集关联方法. 该方法能够动态维护若干描述Pareto 解变化规律的时间序列, 通过对新环境下的Pareto 解集进行预测来生成初始种群. 将LP-DMOEA 应用于非劣分类遗传算法(NSGA2), 并对3 类标准测试函数进行了实验, 所得结果表明该方法能够有...
多项目多资源均衡问题及其基于Pareto的向量评价微粒群算法
Pareto 最优 资源均衡 多项目管理
2014/9/17
首先针对多项目多资源均衡问题的特点, 建立描述问题的多目标优化模型; 然后将Pareto 方法嵌入向量评价微粒群算法(VEPSO), 提出一种新的基于Pareto 的向量评价微粒群算法(VEPSO-BP); 最后利用一个算例测试了VEPSO-BP 的性能, 并与VEPSO 进行了对比. 实验结果表明, VEPSO-BP 的收敛性能优于VEPSO, 实现了对多项目多资源均衡问题的高质量求解.
LAWS OF LARGE NUMBERS FOR TWO TAILED PARETO RANDOM VARIABLES
Almost sure convergence weak law of large numbers strong law of large numbers
2009/9/18
We sample m random variables from a two tailed Pareto
distribution. A two tailed Pareto distribution is a random variable whose
right tail is px−2 and whose left tail is qx−2, where p + ...
Expansions for Quantiles and Multivariate Moments of Extremes for Distributions of Pareto Type
Bell polynomials Extremes Inversion theorem Moments Pareto Quantiles
2010/3/19
Let Xnr be the rth largest of a random sample of size n from a distribution
F(x) = 1 −P∞i=0 cix− −i for > 0 and > 0. An inversion theorem is proved and used to
derive an expan...
ESTIMATING PARETO TAIL INDEX BASED ON SAMPLE MEANS
domain of attraction Pareto index strong embedding of empirical process tailbehavior
2009/2/26
We propose an estimator of the Pareto tail index m of a distribution, that competes well with the Hill, Pickands and moment estimators. Unlike the above estimators,that are based only on the extreme o...
EXPONENTIALITY VERSUS GENERALIZED PARETO——A RESISTANT AND ROBUST TEST
generalized Pareto distribution breakdown point resistance robustness broadened situations mixtures
2009/2/26
Using resistant and robust methods we propose the statistic Tn= (FU−M)/(M−FL)
for testing exponentiality versus generalized Pareto, where FU, FL and M are, respectively,
the upper and lo...
LINKING PARETO-TAIL KERNEL GOODNESS-OFFIT STATISTICSWITH TAIL INDEX AT OPTIMAL THRESHOLD AND SECOND ORDER ESTIMATION
extreme value statistics Pareto-type distribution goodness-of-fit threshold selection
2009/2/25
In this paper the relation between goodness-of-fit testing and the optimal selection of
the sample fraction for tail estimation, for instance using Hill’s estimator, is examined.
We consider this pr...
Muliere and Scarsini’s bivariate Pareto distribution：sums，products，and ratios
incomplete beta function Gauss hypergeometric function Muliere and Scarsini’s bivariate Pareto distribution products of random variables ratios of random variables sums of random variables
2009/2/23
We derive the exact distributions of R = X + Y, P = X Y and W = X/(X + Y) and the corresponding
moment properties when X and Y follow Muliere and Scarsini’s bivariate Pareto distribution. The express...