Large-Scale Multi-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables

The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.

A WEIGHTED ESTIMATE OF THE HORMANDER MULTIPLIER ON THE HEISENBERG GROUP

In this article, the anthors prove the weighted boundedness of Hoermander-type multiplier on the Heisenberg group.

Mining Social Groups with Weighted Similarity in Campus Wireless Network

With the popularity of wireless networks and the prevalence of personal mobile computing devices, understanding the characteristic of wireless network users is of great significance to the network performance. In this study, system logs from two universities, Dartmouth College and Shanghai Jiao Tong University(SJTU), were mined and analyzed. Every user's log was represented by a user profile. A novel weighted social similarity was proposed to quantify the resemblance of users considering influence of location visits. Based on the similarity, an unsupervised learning method was applied to cluster users. Though environment parameters are different, two universities both form many social groups with Pareto distribution of similarity and exponential distribution of group sizes. These findings are very important to the research of wireless network and social network .

Method for multi-attribute group decision-making based on the compromise weights

Multi-attribute group decision-making problems are considered where information on both attribute weights and value scores of consequences is incomplete.In group decision analysis,if preference information about alternatives is provided by participants,it should be verified whether there exist compromise weights that can support all the preference relations.The different compromise weight vectors may differ for the ranking of the alternatives.In the case that compromise weights exist,the method is proposed to find out all the compromise weight vectors in order to rank the alternatives.Based on the new feasible domain of attribute weights determined by all the compromise weight vectors and the incomplete information on value scores of consequences,dominance relations between alternatives are checked by a nonlinear goal programming model which can be transformed into a linear one by adopting a transformation.The checked dominance relations uniformly hold for all compromise weight vectors and the incomplete information on value scores of consequences.A final ranking of the alternatives can be obtained by aggregating these dominance relations.

MULTIPLIERS ON WEIGHTED FUNCTION SPACES OVER LOCALLY COMPACT VILENKIN GROUPS

In this note, we consider the multipliers on weighted function spaces over totally disconnected locally compact abelian groups (Vilenkin groups). Firstly we show an (H1 ,L ) multiplier result. We also give an (Hap ,Hap) multiplier result under a similiar condition of Lu Yang type. In section 2, we obtain a result about the boundedness of multipliers on weighted Besov spaces.

Boundedness of Fractional Maximal Operators on Some of Homogeneous Groups

Let M α be the fractional maximal operators (0<α≤1) and (u,v) a pair of weight functions, u∈D ∞, σ=v~~~~^(-1/(p-1))∈A ∞. The boundedness of M α on some homogenous groups (G, ‖·‖, dx) and the covering Lemma of Calderon-Zygmund type are studied. Not only an adequate covering Lemma of Calderon-Zygmund type is shown, but also the boundedness of fractional maximal operators M α(0<α≤1) on some of homogeneous groups with respect to a given pair of weight functions (u,v) as above is proved. Moreover, a sufficient and necessary condition for M α∈B(u^qdx, v~~pdx), 0<α<1, 1<p<1α, and 1q=1p-α is also given. Finally, an application of the results is also obtained.

Boundedness of Multilinear Singular Integral Operators on Homogeneous Groups

Let G be a homogeneous group. In this paper, the author studies the boundedness of multi-sublinear operators on the product of weighted Lebesgue spaces on G. As its special case, the corresponding result of multilinear Calderon-Zygmund operators can be obtained.

Closed circle DNA algorithm of change positive-weighted Hamilton circuit problem

Chain length of closed circle DNA is equal. The same closed circle DNA＇s position corresponds to different recognition sequence, and the same recognition sequence corresponds to different foreign DNA segment, so closed circle DNA computing model is generalized. For change positive-weighted Hamilton circuit problem, closed circle DNA algorithm is put forward. First, three groups of DNA encoding are encoded for all arcs, and deck groups are designed for all vertices. All possible solutions are composed. Then, the feasible solutions are filtered out by using group detect experiment, and the optimization solutions are obtained by using group insert experiment and electrophoresis experiment. Finally, all optimization solutions are found by using detect experiment. Complexity of algorithm is concluded and validity of DNA algorithm is explained by an example. Three dominances of the closed circle DNA algorithm are analyzed, and characteristics and dominances of group delete experiment are discussed.

Studies in Molecular Weight Determination of Cottonseed and Melon Seed Oils Based Biopolymers

Six grades of biopolymers formulated to have oil content of 40% (M1), 50% (M2), and 60% (M3) melon seed oil (MESO) and 40% (C1), 50% (C2), and 60% (C3) cottonseed oil (COSO) respectively, were prepared with phthalic anhydride, and glycerol using alcoholysis-polycondensation process. The extend of polycondensation was monitored by determining the acid value of aliquots of the reaction mixture at various intervals of time. Molecular weight averages and polydispersity index (PDI) of the finished alkyds were determined by Rast method and end-group analysis. Molecular weight averages and PDI vary with differences in oil length of the alkyds, with samples M2 and C2 respectively exhibiting the highest PDI. Molecular weight average obtained from end-group analysis and those determined by Rast method in brackets are 1338.92 (597.00), 982.33 (696.25), 1316.09 (754.03), and 1160.57 (448.13), 765.96 (583.57), 1049.92 (696.25) for samples M1, M2, M3 and C1, C2, C3 respectively. Number molecular weight averages calculated from end-group analysis are larger than those obtained by Rast method for both MESO and COSO alkyds and seem to grossly overestimate their molecular weights. The mode of variation of these properties indicates that the synthesis of MESO and COSO alkyds are complex. Correlation of PDI with the quality of the finished alkyds shows that the higher the PDI value the better the quality of the alkyd. Performance properties such as rate of drying, film hardness and resistance to chemicals were optimum at 50% oil length for both triglyceride oil alkyds.

基于改进贝叶斯算法的卷烟叶组配方自动管控方法

由于卷烟原料复杂,卷烟叶组配方管控过程中无法准确分析原料之间的关系,提出基于改进贝叶斯算法的卷烟叶组配方自动管控方法。利用传感器并结合数据仓库技术获取历史数据,从中了解卷烟叶组原料的生产条件(输入特征),针对特征参数实施预处理,利用双重加权朴素贝叶斯算法构建管控模型,获取卷烟叶组配方并通过控制器执行配方,实现自动管控。结果表明,所研究方法得出的配方的焦油含量误差小,总氮含量、烟碱含量靠近最佳值2.6%、2.5%,自动控制效果好。

Concave Group Selection of Nonparameter Additive Accelerated Failure Time Model

In this paper, we have studied the nonparameter accelerated failure time (AFT) additive regression model, whose covariates have a nonparametric effect on high-dimensional censored data. We give the asymptotic property of the penalty estimator based on GMCP in the nonparameter AFT model.

可抗穷举攻击的射频识别群组证明协议

针对孙达志等提出的群组证明协议进行重点分析,指出协议存在无法抗穷举攻击的安全缺陷,并在此基础上给出一个改进的协议。协议采用遍历取反运算对信息加密,遍历取反运算将根据加密参量自身汉明重量大小不同而进行对不同参量的取反操作,增加破解难度;协议将信息加密之后再发送,同时信息加密时确保多个参量攻击者无法知晓,以此来抵抗穷举攻击。从安全性角度分析协议,表明协议具有较好的安全性能;从仿真实验角度分析协议,表明协议具有计算量低的优势。

高效低碰撞的太赫兹无线定向MAC协议

针对网络中节点在争用访问时期发送消息碰撞、时隙分配机制低效和空闲时隙浪费等问题,提出了一种高效低碰撞的太赫兹无线定向MAC协议.文中提出了3种新机制,分别是基于缓存权重的分组机制、复用竞争机制以及时隙分配机制.首先,在微网控制器(Piconet Coordinator,PNC)中生成缓存映射表记录节点的缓存情况;然后,根据缓存映射表为节点分组,节点在分组对应的时隙中进行时隙请求,PNC根据节点缓存为节点分配时隙;最后,未申请到时隙的节点利用剩余时隙进行复用竞争操作.仿真结果表明,所提出的方案有效地提高了网络的吞吐量,减少了消息碰撞率并降低了平均时延.

通辽市社区居民老年期痴呆流行病学调查的设计和实施

目的:描述通辽市社区居民老年期痴呆流行病学调查的抽样设计、权重计算、调查工具、现场执行及质量控制方案。方法:采用三阶段不等概率抽样设计在内蒙古自治区通辽市调查65岁及以上的常住居民,采用10/66老年期痴呆系列研究(10/66 Dementia Research Group,10/66 DRG)评估工具获得老年期痴呆的疾病诊断,以计算机辅助个人访谈模式开展调查,并实施调查全程及时质量控制措施。结果:在通辽市9个旗/县/市/区的166个嘎查/村/居中共调查老人4345人,应答率为96.2%。计算抽样设计权数、无应答调整权数和事后分层调整权数后,将上述权数相乘并进行极值调整和标化调整,从而获得最终权数。171名访员接受培训,考核合格后开展入户调查,并采用计算机数据核查、录音核查和电话核查等质量控制措施,保证调查的真实性。结论:本调查采用严格的抽样设计和质量控制措施实施调查,并采用国际效度和信度满意的10/66DRG评估工具作为调查工具,具有国际跨文化可比性,可以为国内其他地区开展老年期痴呆流行病学调查提供方法学参考。

SIMILARITY SOLUTION OF SELF-WEIGHT CONSOLIDATION PROBLEM FOR SATURATED SOIL

A more general assumption than that in the classical one-dimensional large strain consolidation theory is adopted and the exact analytical solution of nonlinear finite strain self-weight consolidation based on this assumption is obtained. By applying the same experimental data, the comparison of the solutions of linear and nonlinear finite strain theory, as well as the numerical calculating results based on finite element method is presented. The results of the comparison show that the analytical solution obtained here takes on better agreement with practical cases than that of linear one, and they also show that, compared with the solutions based on nonlinear theory, the settlement and the consolidation degree based on linear theory are smaller.

智能制造类专业群建设绩效评价机制研究

研究了智能制造类专业群建设绩效评价机制,以提升职业院校智能制造类专业群的建设效果和质量。通过综合文献综述和实证研究,构建了智能制造类专业群建设绩效评价的理论框架,并确定了评价指标体系和权重分配方法。通过问卷调查和数据分析,验证了评价机制的有效性和可行性。研究结果表明,该评价机制能够客观、全面地评估智能制造类专业群的建设绩效,为职业院校提供决策支持和改进方向。

考虑机场、航空公司与空管需求的机场群离场航班时刻优化

随着中国航空流量的不断增加,机场群内航班延误时间长、延误架次多、机场时刻紧张等问题逐渐暴露,这些问题主要是航班时刻设置不合理所导致。为解决这些问题,需要对机场群内航班时刻进行优化。通过从机场、航空公司、空管3个角度综合考虑,分别以延误时间、航空公司航班时刻调整总方差、管制员总调整量作为优化目标,建立了机场群航班时刻优化模型,并使用权重线性递减的粒子群优化算法实现对模型的求解。以京津冀机场群为例进行分析,使用MATLAB对模型进行寻优。结果表明优化后机场群内总延误时间由77580 min减少至46260 min,航空公司航班时刻调整总方差由447.076减少至63.141,管制员总调整量由467次减少至253次,3个目标均得到了优化。可见该模型权衡了机场、航空公司与空管之间的公平性,为机场群航班时刻的优化提供了理论参考。

东方田鼠家群个体体重、攻击性及胆量对其扩散的影响

扩散作为动物适应生存环境的重要特征之一,受到自身生物学特征及环境等方面的制约。以家群形式生活和子代雄鼠扩散为主的东方田鼠,其成员个体是否因领地食物和空间资源竞争导致体重小、攻击性弱及胆小个体先行扩散。以新鲜马唐叶片构建三块密集均质的食物斑块,在食物斑块周边以透明玻璃设置观测箱,采用透明塑胶管连接三块食物斑块作为动物扩散的通道,构建东方田鼠扩散行为观测装置。将东方田鼠家群子代成员投放至带有自身家群气味的食物斑块,测定成员个体在食物斑块上的觅食行为序列过程和参数,以及向其他食物斑块扩散的行为过程和参数以及家群中先行扩散个体体重、攻击性及胆量占所有家群数的比率,检验成员个体的体重、攻击性及胆量对扩散的影响。结果发现,体重小、攻击性弱和胆小个体的觅食启动时间极显著地大于体重大、攻击性强和胆大个体的,但其先行扩散的比率却显著地大于体重大、攻击性强和胆大个体的;然而体重小、攻击性弱及胆小个体的扩散开始时间显著或极显著地大于体重大、攻击性强及胆大个体的。结果揭示,东方田鼠家群成员随着年龄的增长和对食物及空间资源竞争的加剧,体重大、攻击性强及胆大个体会迫使体重小、攻击性弱及胆小个体先行扩散。

区间粗糙数群组G1法的随机聚合求解及应用

针对复杂不确定环境下的群体评价问题,采用区间粗糙数表征专家偏好,在G1法的基础上,结合蒙特卡洛仿真技术,提出了一种随机模拟聚合算法.首先,通过随机抽样的方式模拟权重系数,并依据序相关性和区间粗糙数贴近度确定专家权重.其次,综合所有专家意见得到指标的最终权重,并将其与预处理后的指标值线性集结,求得一次模拟的综合评价值,据此判断被评价对象间的优劣.通过充分模拟得出优胜度矩阵,并从中推导出包含优胜概率的可能性排序,弥补了不确定信息环境下绝对排序呈现的不足.最后,通过算例说明了方法的有效性,并与现有方法对比阐述了所提方法的优势.