ad hoc网络中基于离散粒子群优化的权重分簇算法

针对移动性较强的adhoc网络,提出了一种基于离散粒子群优化的权重分簇算法。该算法通过引入节点局部密度,仅利用节点局部拓扑信息来计算权重,然后通过离散粒子群优化簇头选举。在保证网络负载平衡的情况下,最大限度确保网络稳定性。仿真试验表明,与典型的权重分簇算法WCA比较,该算法提高了移动adhoc网络的稳定性,同时网络生命周期平均提高了88.28%。

基于对数平均权重分解法的我国二氧化碳排放因素分解研究

二氧化碳是最主要的温室气体，控制二氧化碳排放对于实现我国碳强度目标具有重要意义。本文以1997～2010年的相关统计数据为基础，基于对数平均权重分解法（LMDI）构建了二氧化碳排放的指数分解模型，并采用该模型将我国当前的二氧化碳排放总量分解为11种不同的影响因素。然后通过分析和计算得出了各省的经济产出、人均GDP和城镇化水平等正向影响因素对二氧化碳排放的增长起到促进作用，而各部门的能源消费强度、农村人口比重、各省部门结构比重等负向影响因素对二氧化碳排放的增长起到抑制作用。最后根据对模型的分析指出了我国二氧化碳减排的发展方向，以期为二氧化碳减排的实践提供有益借鉴。

权重分位数-自适应LASSO方法研究与应用

有关惩罚分位数回归的研究较为丰富,不过多数惩罚分位数回归模型并没有解决杠杆点问题,WLAD-LASSO能有效处理自变量存在的离群值,是惩罚分位数回归的特例.该文将WLAD-LASSO推广至更一般的情形,提出了WQR-LASSO方法.WQR-LASSO不仅具备WLAD-LASSO的优点,而且无须对误差分布做任何假设,能更加全面地反映自变量对因变量不同分位点的影响,同时实现稳健的参数估计和变量选择.模拟结果表明,相较于自适应LASSO和中位数-自适应LASSO方法,WQR-LASSO的正确拟合率基本为100%,均方差大多小于1,在有限样本上表现更好.实证分析表明,运用WQR-LASSO对波士顿都会区的房产进行估价,与特征价格模型和机器学习方法中备受好评的随机森林方法相比,WQR-LASSO提供的估价结果准确性较高,变量选择能力也最强.

电力生产CO_2排放变化影响因素分解

利用对数平均权重分解法(LMDI)构建了电力生产CO_2排放变化影响因素的分解模型,并利用1985—2009年中国能源平衡表中的数据测算出电力生产CO_2排放量。在此基础上,将该CO_2排放量变化分解为收入效应、电力生产强度效应、电力生产结构效应、人口效应和发电煤耗效应。以1985年为基期并以我国国民经济和社会发展的五年规划为分解区间对这些影响因素进行分解分析.考察各种影响因素变动的背后原因。结合实证分析,给出相应的政策建议。

公平合理选课方式的探讨

教学资源相对紧张是目前情况下我国绝大多数高校都同样面临的问题。教师资源、教室资源直接制约着选课工作。每个高校根据自己的实际情况,一般会有不同的选课方式。目前主要的选课方式有两种:“抽签”和“先来先得”。文章对这两种方式进行深入分析,并证明这两种方式实际上都不能很好地解决学生最关心的问题,那就是“公平”。

基于AHP的多视角信息化绩效评价方法研究

企业信息化作为国家信息化的基础和核心,既是创造经济财富的主要力量,也是推进信息化进程的重要力量。军工企业每年信息化的巨额投入,以及信息化所面临的巨大风险,使得各军工企业、各集团及政府机关不得不关注信息化的战略投资收益以及绩效管理等深层次的问题。

能源强度、产业结构及低碳政策选择

气候变化日益严重,分析碳排放的影响因素,探讨工业碳减排意义重大。运用对数平均权重分解法(LMDI)的加和分解法建立了能源消耗碳排放的因素分解模型,从能源强度、产业结构、能源结构、经济产出和从业人口规模等5个方面对安徽省规模以上工业行业的碳排放进行实证分析。结果显示:能源强度、产业结构对碳排放有着较强的负效应,经济产出、从业人口规模有强的正效应,能源结构表现出不显著的正效应。安徽工业行业中,电力、热力生产和供应业,煤炭开采和洗选业,石油加工、炼焦和核燃料加工业,黑色金属冶炼和压延加工业及非金属矿物制品业这五大高能源强度是影响安徽省工业碳排放的最主要行业。为降低碳排放,有针对性地提出了降低能源强度,调整产业结构及减少五大行业的比重的政策建议。

层次分析法在房屋结构可靠性评估中的应用

以砌体结构房屋为例,建立了可靠性影响因素的递阶层次结构模型,在专家咨询的基础上,形成两两比较判断矩阵,应用层次分析法确定砌体结构房屋可靠性影响因素的权重。该方法可有效地淡化人为因素的影响,使权重确定结果更加科学、合理。

关于中学数学好题特征的调查研究

通过调查的方法研究综合性考试和单元考试中好题的特征，建立各特征的权重分以比较各特征的重要性．在此基础上，考察了一道2011年上海高考题的特征分，并得出该题是较好题的结论．

Comprehensive evaluation method for superstructures of prestressed concrete girder bridges

A multi-level evaluation model for the superstructure of a damaged prestressed concrete girder or beam bridge is established, and the evaluation indices of the model as well as the rating standards are defined. A normal relative function about the evaluation indices of each element is developed to calculate the relative degree, and for each element there are no sub-level elements. When evaluating the elements in the sub-item level or the index level of the model, the weights of elements pertain to one adopted element, taking into account their degrees of deterioration. Since the relative degrees and structure evaluation scales on the damage conditions are applied to characterize the superstructure of damaged prestressed concrete girder bridges, this method can evaluate the prestressed structure in detail, and the evaluation results agree with the Code for Maintenance of Highway Bridges and Culvers （JTG Hll--2004 ）. Finally, a bridge in Jilin province is taken as an example, using the method developed to evaluate its damage conditions, which gives an effective way for bridge engineering.

Variations and Controlling Factors of the Coccolith Weight in the Western Pacific Warm Pool over the Last 200 ka

Using a coccolith weight analytic software(Particle Analyser), we analyze most abundant coccolith species in a sediment core from the central Western Pacific Warm Pool(WPWP) and calculate coccolith size and weight variations over the last 200 ka. These variations are compared with the trends of sea surface temperature(SST), primary productivity(PP), sea surface salinity(SSS), and insolation. Our results demonstrate that the size and weight of the coccoliths varied in response to variations of these factors, and their average total weight is primarily related to the relative abundance of the dominant species GEO(Gephyrocapsa oceanica). The variation in weight of EMI(Emiliania huxleyi) and GEE(Gephyrocapsa ericsonii) are mainly influenced by nutrients, and the variation of GEM(G. muellerae conformis) and GEO(G. oceanica) weight are mainly influenced by SST. For all of the taxa weight, PP and SST present apparent precession or semi-precession cycles, we consider that the mono-coccolith weight of the Equatorial Western Pacific is primarily affected by precession drived thermocline and nutricline variation.

Fuzzy Ontology Construction Based on Incomplete Knowledge

There exists widely incomplete knowledge all over the world, but incomplete knowledge still cannot be dealt with in the process of ontology construction. Hence, a method for fuzzy ontology construction based on incomplete knowledge is proposed. First, the calculation principle of the attribute weight of the ontology concept is presented, and the calculation function of the attribute weight is derived through experiments. Then, the membership degree of the incomplete individual to the concept is computed. Finally, the incomplete individual is classified according to the principle of the variable precision rough set model. The experimental results show that the average precision of the classification of the incomplete individuals is 81.7% when the common attributes are omitted and that it is difficult to classify the incomplete individuals correctly when the private attributes are omitted. This method is significant for handling incomplete knowledge in the process of ontology construction.

Improved random noise attenuation using f-x empirical mode decomposition and local similarity

Conventional f-x empirical mode decomposition（EMD） is an effective random noise attenuation method for use with seismic profiles mainly containing horizontal events.However,when a seismic event is not horizontal,the use of f-x EMD is harmful to most useful signals.Based on the framework of f-x EMD,this study proposes an improved denoising approach that retrieves lost useful signals by detecting effective signal points in a noise section using local similarity and then designing a weighting operator for retrieving signals.Compared with conventional f-x EMD,f-x predictive filtering,and f-x empirical mode decomposition predictive filtering,the new approach can preserve more useful signals and obtain a relatively cleaner denoised image.Synthetic and field data examples are shown as test performances of the proposed approach,thereby verifying the effectiveness of this method.

The exploration of middle managers＇ performance evaluation indicators

The core role of middle managers in the enterprises, plays an important role in the whole enterprise. Yet all round the teacher talked about a lot of companies, including layer of managers＇ performance status is not as good as executives expected. This paper mainly studies the present enterprise, the real role of middle managers, and their performance status, and middle managers in the performance of the existing problems and the analysis of the present situation of the listed in the reason, and put forward relevant countermeasures according to the actual situation. The results show that the middle managers performance evaluation become a mere formality, most managers see performance appraisal as a burden and form; Middle managers set of assessment index and the use of problems; The right job analysis is the key to design middle managers performance evaluation indicators; In the proper selection of performance indicators is significant for middle managers to improve performance; Performance indicators weights allocation to improve the teaching quality of middle managers performance influence; Design middle tube is the main body of performance appraisal index of middle performance increase.

Evaluating gravity gradient components based on a reweighted inversion method

In gravity gradient inversion,to choose an appropriate component combination is very important,that needs to understand the function of each component of gravity gradient in the inversion.In this paper,based on the previous research on the characteristics of gravity gradient components,we propose a reweighted inversion method to evaluate the influence of single gravity gradient component on the inversion resolution The proposed method only adopts the misfit function of the regularized equation and introduce a depth weighting function to overcome skin effect produced in gravity gradient inversion.A comparison between different inversion results was undertaken to verify the influence of the depth weighting function on the inversion result resolution.To avoid the premise of introducing prior information,we select the depth weighting function based on the sensitivity matrix.The inversion results using the single-prism model and the complex model show that the influence of different components on the resolution of inversion results is different in different directions,however,the inversion results based on two kind of models with adding different levels of random noise are basically consistent with the results of inversion without noises.Finally,the method was applied to real data from the Vinton salt dome,Louisiana,USA.

Construction and Application of Oral English Evaluation Index System Based on AHP

The paper confirms evaluation indexes of oral English with the application of Delphi technique and expert consultation, and then establishes hierarchical structure model of oral English evaluation index system. The weight of each evaluation index is determined with the methods of Delphi and expert consultation again. A group of students＇ oral English is subsequently evaluated by using AHP （Analytic Hierarchy Process） based on oral English evaluation index system and the weights we set up in this thesis.

Modeling Evolution of Weighted Clique Networks

We propose a weighted clique network evolution model, which expands continuously by the addition of a new clique （maximal complete sub-graph） at. each time step. And the cliques in the network overlap with each other. The structural expansion of the weighted clique network is combined with the edges＇ weight and vertices＇ strengths dynamical evolution. The model is based on a weight-driven dynamics and a weights＇ enhancement mechanism combining with the network growth. We study the network properties, which include the distribution of vertices＇ strength and the distribution o~ edges＇ weight, and find that both the distributions follow the scale-free distribution. At the same time, we also find that the relationship between strength and degree of a vertex are linear correlation during the growth of the network. On the basis of mean-field theory, we study the weighted network model and prove that both vertices＇ strength and edges＇ weight of this model follow the scale-free distribution. And we exploit an algorithm to forecast the network dynamics, which can be used to reckon the distributions and the corresponding scaling exponents. Furthermore, we observe that mean-field based theoretic results are consistent with the statistical data of the model, which denotes the theoretical result in this paper is effective.

New Keynesian Model and Inflation Prediction

Recently, much dispute has occurred about the validity of the New Keynesian model from both theoretical and empirical views. However, a few studies have analyzed this model from the empirical perspective. Few other studies have analyzed this model directly or nearly directly. This article empirically examines the New Keynesian model focusing on inflation forecast. Generalized method of moments （GMM） is used to examine whether the typical Keynesian model with Taylor rule is empirically appropriate for the US, UK, Euro area, and Japan. The results showed： （1） the New Keynesian model fits well in most cases and explains the real economy well. Taylor rule also fits well for most cases; （2） Rational expectations for inflation rates may not be useful based on this model When AR （1） （time series analysis） model is used to capture inflation expectations instead of one-time ahead real values, the model fits well. With measured expectations, the relative weight of the forward-looking terms increase on the cost of lagged inflation and output terms, even up to the point at which the lagged inflation terms are no longer needed to rescue the new Keynesian model; and （3） Forward-looking variables play more important roles than backward-looking ones in economic activity. Results with expectations with forward-looking terms perform better in general. This New Keynesian model may reduce the importance of lagged output in some cases

Free Energy Level Correction by Monte Carlo Resampling with Weighted Histogram Analysis Method

Free energy calculations may provide vital information for studying various chemical and biological processes.Quantum mechanical methods are required to accurately describe interaction energies,but their computations are often too demanding for conformational sampling.As a remedy,level correction schemes that allow calculating high level free energies based on conformations from lower level simulations have been developed.Here,we present a variation of a Monte Carlo(MC)resampling approach in relation to the weighted histogram analysis method(WHAM).We show that our scheme can generate free energy surfaces that can practically converge to the exact one with sufficient sampling,and that it treats cases with insufficient sampling in a more stable manner than the conventional WHAM-based level correction scheme.It can also provide a guide for checking the uncertainty of the levelcorrected surface and a well-defined criterion for deciding the extent of smoothing on the free energy surface for its visual improvement.We demonstrate these aspects by obtaining the free energy maps associated with the alanine dipeptide and proton transfer network of the KillerRed protein in explicit water,and exemplify that the MC resampled WHAM scheme can be a practical tool for producing free energy surfaces of realistic systems.

Weighted High Order Poincaré Inequalities on Stratified Lie Groups

In this paper,we focus on studying weighted Poincare inequalities on stratified Lie groups.We derive various Poincaréinequalities in the case 1<p=q<∞ in the high order Sobolev space Wm,p.We derive several Poincare inequalities that complement existing results,which have only been proved for the case 1<p<q<∞.