基于均匀设计抽样遗传算法求解背包问题

众所周知,遗传算法的运行机理及特点是具有定向制导的随机搜索技术,其定向制导的原则是:导向以高适应度模式为祖先的"家族"方向.以此结论为基础,利用均匀设计抽样的理论和方法,对遗传算法中的交叉操作进行了重新设计,给出了一个新的GA算法,称之为均匀设计抽样遗传算法.最后将均匀设计抽样遗传算法应用于求解背包问题,并与简单遗传算...     

随机化均匀设计在股票交易上的应用

本文首先利用Bundschuh和朱尧辰(1993)的偏差精确计算公式,给出了某些二维均匀设计的生成元.其次,利用随机化均匀设计提出了一种可以提高以移动平均线进行股票交易的赚钱概率的方法.     

随机化均匀设计及其在股票交易上的应用

本文首先利用Bundschuh和朱尧辰（1993）的偏差计算公式,给出了构造某些非平衡均匀设计方法及相应的均匀设计表,之后把随机化均匀设计与移动平均线相结合,给出了移动平均线的最佳参数组合。     

均匀设计抽样的偏差

该文证明了均匀设计抽样点集的偏差为O（n－1（lnn）d），另外也证明了随机化均匀设计点集的偏差有同样的阶．最后进行了随机模拟．     

均匀设计抽样的一、二阶矩

（７）中给出并研究了均匀设计抽样（ＵＤＳ）及随机化均匀设计（ＲＵＤ）的一些优良性质,作者给出该设计和抽样的一、二阶矩。     

混料均匀设计 *

考虑混料试验设计:0≤a_i<x_i<b_i≤1,1≤i≤s,x₁+…+x_s=1,此处a_i,b_i,1≤i≤s为给予常数,用数论中的一致分布理论对这一模型提供一个处理方法.     

基于遗传算法和模拟退火的插值马氏模型用于真核生物启动子识别

启动子识别是生物信息学领域极具挑战的问题.本文在IMC(Interpolated Markov Chin)的框架下考虑碱基的插入与缺失,采用SA(Simulated Annealing)训练转移概率,以增加模型的鲁棒性,利用GA(Genetic Algorithm)优化IMC插值系数,以克服梯度算法易于陷入局部极值点的缺陷,最后将该模型用于启动子识别,识别率在测试集达到86%.     

基于遗传算法和神经网络的注塑工艺参数优化

基于Moldflow模拟仿真的结果,结合GA算法优化BP网络的结构,建立了模具温度,熔体温度,保压压力,注射速度等工艺参数与塑件体积收缩率的BP网络模型.获得了最优的工艺参数组合,同时预测结果与实际结果吻合.通过神经网络算法(BP)预测注塑工艺参数对塑件质量的影响,可以有效降低其他建模方法的难度和工作量,方法可以推广到塑件其他质量预测过程中.     

混料均匀设计

本文详细讨论了获得混料均匀设计表的三种方法——变换法、迭代法和循环拉丁方型方法。作为迭代法的结果,在附录,本文给出了试验次数为4≤n≤11的改进后的混料均匀设计表。     

均匀设计及其应用

均匀设计及其应用方开泰编者按：最近内刊上记者以标题“我国独创的“均匀设计”在国际领先，其社会经济效益不可估量”报导了均匀设计在飞航导弹及国民经济的应用及其潜在的重要作用，建议在我国采取计划推广与市场推广相结合的办法．本刊很高兴邀请均匀设计的发明人之一...     

Perfect matchings in random uniform hypergraphs

Let ??_k(n, p) be the random k‐uniform hypergraph on V = [n] with edge probability p. Motivated by a theorem of Erd?s and Rényi 7 regarding when a random graph G(n, p) = ??₂(n, p) has a perfect matching, the following conjecture may be raised. (See J. Schmidt and E. Shamir 16 for a weaker version.) Conjecture. Let k|n for fixed k ≥ 3, and the expected degree d(n, p) = p(). Then (Erd?s and Rényi 7 proved this for G(n, p).) Assuming d(n, p)/n^1/2 → ∞, Schmidt and Shamir 16 were able to prove that ??_k(n, p) contains a perfect matching with probability 1 ? o(1). Frieze and Janson 8 showed that a weaker condition d(n, p)/n^1/3 → ∞ was enough. In this paper, we further weaken the condition to A condition for a similar problem about a perfect triangle packing of G(n, p) is also obtained. A perfect triangle packing of a graph is a collection of vertex disjoint triangles whose union is the entire vertex set. Improving a condition p ≥ cn^?2/3+1/15 of Krivelevich 12 , it is shown that if 3|n and p ? n^?2/3+1/18, then © 2003 Wiley Periodicals, Inc. Random Struct. Alg., 23: 111–132, 2003     

A note on Hamiltonicity of uniform random intersection graphs

We consider a collection of n independent random subsets of [m] = {1, 2, . . . , m} that are uniformly distributed in the class of subsets of size d, and call any two subsets adjacent whenever they intersect. This adjacency relation defines a graph called the uniform random intersection graph and denoted by G _n,m,d . We fix d = 2, 3, . . . and study when, as n,m → ∞, the graph G _n,m,d contains a Hamilton cycle (the event denoted \( {G_{n,m,d}} \in \mathcal{H} \)). We show that \( {\mathbf{P}}\left( {{G_{n,m,d}} \in \mathcal{H}} \right) = o(1) \) for d ² nm ^?1 ? lnm ? 2 ln lnm → ?∞ and \( {\mathbf{P}}\left( {{G_{n,m,d}} \in \mathcal{H}} \right) = 1 - o(1) \) for 2nm ^?1 ? lnm ? ln lnm → +∞.     

A note on the sum of uniform random variables

An inductive procedure is used to obtain distributions and probability densities for the sum S_n of independent, non-equally uniform random variables. Some known results are then shown to follow immediately as special cases. Under the assumption of equally uniform random variables some new formulas are obtained for probabilities and means related to S_n. Finally, some new recursive formulas involving distributions are derived.     

A note on random greedy coloring of uniform hypergraphs

The smallest number of edges forming an n‐uniform hypergraph which is not r‐colorable is denoted by m(n,r). Erd?s and Lovász conjectured that . The best known lower bound was obtained by Radhakrishnan and Srinivasan in 2000. We present a simple proof of their result. The proof is based on the analysis of a random greedy coloring algorithm investigated by Pluhár in 2009. The proof method extends to the case of r‐coloring, and we show that for any fixed r we have improving the bound of Kostochka from 2004. We also derive analogous bounds on minimum edge degree of an n‐uniform hypergraph that is not r‐colorable. © 2014 Wiley Periodicals, Inc. Random Struct. Alg., 47, 407–413, 2015     

Extremal uniform distribution and random chord lengths

This paper generalizes earlier results on the behaviour of uniformly distributed sequences in the unit interval [0,1] to more general domains. We devote special attention to the most interesting special case [0,1] ^d . This will naturally lead to a problem in geometric probability theory, where we generalize results by Anderssen, Brent, Daley and Moran about random chord lengths in high-dimensional unit cubes, thereby answering a question by Bailey, Borwein and Crandall.     

Connectivity of the uniform random intersection graph

A uniform random intersection graphG(n,m,k) is a random graph constructed as follows. Label each of n nodes by a randomly chosen set of k distinct colours taken from some finite set of possible colours of size m. Nodes are joined by an edge if and only if some colour appears in both their labels. These graphs arise in the study of the security of wireless sensor networks, in particular when modelling the network graph of the well-known key predistribution technique due to Eschenauer and Gligor.The paper determines the threshold for connectivity of the graph G(n,m,k) when n→∞ in many situations. For example, when k is a function of n such that k≥2 and m=⌊n^α⌋ for some fixed positive real number α then G(n,m,k) is almost surely connected when

lim infk²n/mlogn>1,     

Almost perfect matchings in random uniform hypergraphs

We consider the following model H_r(n, p) of random r-uniform hypergraphs. The vertex set consists of two disjoint subsets V of size | V | = n and U of size | U | = (r − 1)n. Each r-subset of V × (_r−1^U) is chosen to be an edge of H ε H_r(n, p) with probability p = p(n), all choices being independent. It is shown that for every 0 < < 1 if P = (C ln n)/n^r−1 with C = C() sufficiently large, then almost surely every subset V₁ V of size | V₁ | = (1 − )n is matchable, that is, there exists a matching M in H such that every vertex of V₁ is contained in some edge of M.     

Random strict convexity and random uniform convexity in random normed modules

Based on the analysis of stratification structure on random normed modules, we first present random strict convexity and random uniform convexity in random normed modules. Then, we establish their respective relations to classical strict and uniform convexity: in the process some known important results concerning strict convexity and uniform convexity of Lebesgue-Bochner function spaces can be obtained as a special case of our results. Further, we also give their important applications to the theory of random conjugate spaces as well as best approximation. Finally, we conclude this paper with some remarks showing that the study of geometry of random normed modules will also motivate the further study of geometry of probabilistic normed spaces.