居民垃圾分类行为与政府收费行为的演化博弈分析

为探究政府垃圾收费政策在居民实施垃圾分类中的作用,本文在分析政府和居民在不同策略下各自成本和收益的基础上,借助演化博弈论方法构建居民和政府的演化博弈模型,研究了演化稳定策略,并进行仿真分析。结果表明,居民的垃圾分类行为与环保意识、政府的收费政策等有关,政府可以通过设立合理的垃圾收费政策和加强宣传来引导居民进行垃圾分类。     

北京市居民垃圾分类情况调查浅析

采用调查问卷的形式,对北京市泰和小区、贵园南、北小区的居民和亦庄中心小学的家长进行垃圾分类知识的掌握情况,垃圾分类的态度意识,以及其对垃圾分类的处理方式等相关方面的了解.本文通过Pearson卡方检验来分析三个小区垃圾分类问题上的差异性;通过logistic回归,建立垃圾分类问题中居民的垃圾分类行为、居民的垃圾分类态度与垃圾分类知识的掌握情况之间的关系;同时,通过调查问卷来分析民众是否正确进行垃圾分类,并且分析民众将垃圾错误分类的原因何在,并提出合理有效措施以确保民众能够更好地进行垃圾分类.     

基于集对分析的城市居民幸福指数测评—以济南、青岛、泰安、滨州为例

为探讨城市居民幸福感及其影响因素,采用主、客观评价相结合的方法构建了城市居民幸福指数的评价模型.首先通过对经济发展、居民生活、人口与就业结构和生活环境水平四个方面构建了居民客观幸福指数评价指标体系.对身心健康、生活便利、环境舒畅状况和自我价值实现四个方面构建了居民主观幸福指数评价指标体系.然后运用变异系数、主观G1权重赋值、集对分析评价法建立了一种基于多元联系数的综合评价模型.最后以济南、青岛、泰安、滨州为例,阐述了城市居民幸福指数集对分析模型的评价过程,评价结果合理可靠.     

基于演化博弈的垃圾分类管理策略研究

国内外研究经验表明，垃圾分类是缓解环境问题的重要举措。但是现行的垃圾分类激励机制存在居民负担重、推广阻力大等问题。本文提出将垃圾分类所得绿色积分与碳交易机制相结合的新型激励机制，并应用演化博弈理论建立了政府、企业与居民之间的三方非合作博弈模型，最终通过数值模拟量化分析关键参数对三方主体决策的影响。结果表明：(1)最终的演化均衡结果是：政府选择本文设计的垃圾分类积分机制、企业选择激进生产、居民选择执行垃圾分类；(2)通过数值模拟得出：(1)在积分机制下，政府可以通过增加10%以内的宣传监管投入或40%以内的企业补贴来推进演化过程；(2)居民的积分收益减少在30%以内、时间与体力支出增加在15%以内，仍应执行垃圾分类；(3)企业的额外产值收益减少在10%以内、积分价格增加在75%以内，仍会采取激进生产。因此，本文提出的积分机制相较于现行机制更具优势，有望为我国生活垃圾分类机制建设与循环经济发展提供决策支持。     

MOOC视频学习行为大数据分析

分析了MOOC观看视频行为数据的特征和影响学习者持续观看视频的因素,以及MOOC最受欢迎视频时长的分析方法.研究结果表明MOOC观看视频行为数据具有稀疏性和低秩的特点,在MOOC观看视频行为数据中包含了大量无效的学习行为;影响学习者持续观看视频的因素很多,且相互独立,不存在主导因素.本研究对促进MOOC课程的建设和发展有积极的作用.     

制造型企业基层管理者工作满意度对工作倦怠的影响实证分析

本文旨在探讨制造型企业基层管理者工作满意度对工作倦怠的影响。先运用2次预调查的数据分别对MBI-GS和工作满意度量表进行了探索性和验证性因素分析,然后利用验证的量表对21家制造型企业进行了调查。相关分析表明,工作满意度及其4个维度工作任务、领导行为、薪酬与工作环境、晋升与发展同情绪衰竭和消极怠慢都呈显著负相关,同职业效能感都呈显著正相关。分层回归分析表明,工作满意度的4个维度对消极怠慢都有显著的负向影响,对职业效能感都有显著的正向影响;领导行为、工作任务、薪酬与工作环境对情绪衰竭都有显著的负向影响。在工作满意度4个维度中,领导行为对情绪衰竭和消极怠慢的影响最大,工作任务对职业效能感的影响最大。     

基于模糊影响图的我国居民消费水平的评价研究

为了评价我国居民消费水平的变动及其影响因素之间的相互作用及影响,本文运用模糊影响图的方法,从需求方面、基础设施、经济环境、政策环境以及消费者自身五个方面选取了影响消费的十六个指标,并对这些指标进行评价分析。结果表明,我国居民消费水平增长幅度缓慢,无明显变化。根据这一评价结果,结合消费影响因素影响图的拓扑结构得出,对外开放程度、社会保障水平、消费习惯以及居民受教育程度是导致消费增长缓慢的主要原因,进而提出对策建议。为今后提高我国居民消费水平方面的研究和我国相关政策的实施提供了理论借鉴和实践指导。     

客户价值研究及其对客户关系管理绩效的影响

客户价值研究是客户关系管理研究中的重要内容，本基于客户视角对客户价值进行分析，提出客户价值应包含五个关键维度：功能价值、社会价值、情感价值、知识价值和感知牺牲。同时建立了客户价值对基于客户行为的客户关系管理(CRM)绩效的影响理论模型并提出相关假设，然后通过实证分析验证该假设，最后讨论了实证结果及其对客户关系管理实践的指导意义。     

西安市城市居民生活用水量的实证分析

基于多元回归分析方法,以西安市为例,探讨影响城市生活用水量的影响因素,建立了基于多元线性回归分析的城市生活用水模型,并且采用来自《西安统计年鉴》的统计数据作为样本,进行实证分析.通过回归拟合结果分析证明,城市居民人口和居住面积两项指标对城市生活用水量的影响最为显著,研究结果证实了所建立的模型回归效果显著,误差较小,结果令人满意.     

品牌体验对品牌忠诚的影响机制分析——基于餐饮品牌的实证研究

本文以餐饮品牌为研究对象,探讨了包括感官体验、情感体验和关联体验三个维度的品牌体验对品牌忠诚的影响机制,基于对388份问卷数据的分析,我们发现:除感官体验维度对态度忠诚存在直接的正向影响之外,品牌体验的其他各维度对态度忠诚和行为忠诚均无直接作用;品牌体验的三个维度均可通过感知价值和顾客满意对品牌忠诚产生间接影响,其中感官体验的效应最大,其次为情感体验,关联体验相对较低。     

Hybrid linear and nonlinear complexity pursuit for blind source separation

Blind source separation (BSS) is an increasingly popular data analysis technique with many applications. Several methods for BSS using the statistical properties of original sources have been proposed; for a famous case, non-Gaussianity, this leads to independent component analysis (ICA). In this paper, we propose a hybrid BSS method based on linear and nonlinear complexity pursuit, which combines three statistical properties of source signals: non-Gaussianity, linear predictability and nonlinear predictability. A gradient learning algorithm is presented by minimizing a loss function. Simulations verify the efficient implementation of the proposed method.     

基于降低失效停放区比率的共享单车系统稳定性研究

共享单车失效停放区使得用户无法取车或还车,影响共享单车系统运营稳定性。本文基于排队论与马尔科夫链构建了共享单车系统稳定状态平均场方程组并求解稳态解,发现停放区交互作用使得失效停放区对相邻停放区产生需求溢出效应,增加系统失效停放区比率,影响系统运营稳定性。本文以降低系统失效停放区比率目标,引入(M,S)交互策略,调节失效停放区对相邻停放区的交互作用程度。进一步,以算例分析比较相同类型与不同类型停放区交互作用、(M,S)交互策略下共享单车系统的失效停放区比率。结果表明(M,S)交互策略能够有效降低失效停放区比率,提高系统运营稳定性。本研究为共享单车企业运营稳定性决策提供了有价值的参考。     

基于规范高阶累积量的盲分离算法

本文给出信号的r阶规范累积量定义,证明了在信号瞬时线性混叠情况下r阶规范累积量绝对值不超过最大源信号的r阶规范累积量,因此可以通过最大化r阶规范累积量的绝对值实现盲分离.最大化r阶规范累积量的绝对值可以得到两种盲分离算法,一种高效快速算法———特征值分解盲分离算法,另外一种盲提取算法.本文为高阶累积量盲分离奠定了严格的理论基础.仿真结果验证了理论的正确性和算法的有效性.     

A comparative numerical analysis for the guillotine two-dimensional cutting problem

In this work, the behavior of four algorithms in the resolution of the two-dimensional constrained guillotine cutting problem is analyzed. This problem is concerned about the way a set of pieces should be cut from a plate of greater dimensions, considering guillotine cutting and a constrained number of times a piece can be cut from the plate. In this study three combinatorial and two heuristic methods are considered. In the combinatorial methods from the set of pieces, a minimum loss layout is constructively generated based on Wang's algorithm. In addition, an evolutionary and an annealing type approach are considered. All of these models have been implemented on a high performance Silicon Graphics machine. Performance of each algorithm is analyzed both in terms of percentage waste and running time. In order to do that, a set of 1000 instances are classified according to their combinatorial degree and subsequently evaluated. This revised version was published online in June 2006 with corrections to the Cover Date.     

中国制造业实施六西格玛管理的成功关键要素分析

自摩托罗拉公司于1987年提出六西格玛概念以来,六西格码管理已逐渐成为质量改进的主流方法之一。尽管不少学者和咨询专家对实施六西格玛管理的成功关键要素进行了探讨,但都是基于理论分析或定性描述。本文在综述国内外相关研究文献的基础上,提出了实施六西格玛管理的成功要素概念模型,并通过调查问卷和利用结构方程模型,对中国制造业实施六西格玛管理的关键成功要素进行了实证分析。研究结果表明:领导层的高度关注,建立并实施合适的六西格玛战略,以顾客和市场为关注焦点,并通过有效的成果测量、评价和奖励方法,选择、管理和实施六西格玛项目是实施六西格玛管理的关键成功要素;同时,本文也分析了这些要素之间的因果关系。     

A fixed-point algorithm for blind source separation with nonlinear autocorrelation

This paper addresses blind source separation (BSS) problem when source signals have the temporal structure with nonlinear autocorrelation. Using the temporal characteristics of sources, we develop an objective function based on the nonlinear autocorrelation of sources. Maximizing the objective function, we propose a fixed-point source separation algorithm. Furthermore, we give some mathematical properties of the algorithm. Computer simulations for sources with square temporal autocorrelation and the real-world applications in the analysis of the magnetoencephalographic recordings (MEG) illustrate the efficiency of the proposed approach. Thus, the presented BSS algorithm, which is based on the nonlinear measure of temporal autocorrelation, provides a novel statistical property to perform BSS.     

Blind source separation with nonlinear autocorrelation and non-Gaussianity

Blind source separation (BSS) is a problem that is often encountered in many applications, such as biomedical signal processing and analysis, speech and image processing, wireless telecommunication systems, data mining, sonar, radar enhancement, etc. One often solves the BSS problem by using the statistical properties of original sources, e.g., non-Gaussianity or time-structure information. Nevertheless, real-life mixtures are likely to contain both non-Gaussianity and time-structure information sources, rendering the algorithms using only one statistical property fail. In this paper, we address the BSS problem when source signals have non-Gaussianity and temporal structure with nonlinear autocorrelation. Based on the two statistical characteristics of sources, we develop an objective function. Maximizing the objective function, we propose a gradient ascent source separation algorithm. Furthermore, We give some mathematical properties for the algorithm. Computer simulations for sources with square temporal autocorrelation and non-Gaussianity illustrate the efficiency of the proposed approach.     

NMF versus ICA for blind source separation

Blind source separation (BSS) is a problem of recovering source signals from signal mixtures without or very limited information about the sources and the mixing process. From literatures, nonnegative matrix factorization (NMF) and independent component analysis (ICA) seem to be the mainstream techniques for solving the BSS problems. Even though the using of NMF and ICA for BSS is well studied, there is still a lack of works that compare the performances of these techniques. Moreover, the nonuniqueness property of NMF is rarely mentioned even though this property actually can make the reconstructed signals vary significantly, and thus introduces the difficulty on how to choose the representative reconstructions from several possible outcomes. In this paper, we compare the performances of NMF and ICA as BSS methods using some standard NMF and ICA algorithms, and point out the difficulty in choosing the representative reconstructions originated from the nonuniqueness property of NMF.     

异维混沌动力系统的有限时间广义同步

本文研究了异维混沌动力系统的有限时间广义同步的问题.利用有限时间Lyapunov稳定性定理、Jensen不等式等理论方法,通过设置不同的控制器,从理论上提出了一般的异维驱动系统和响应系统的有限时间广义同步的两种方案,并且对方案二中的影响同步时间因素做了理论分析和证明.最后,数值模拟验证了提出理论的正确性和可行性.     

Cyclic cellular automata in 3D

Cyclic cellular automata in two dimensions have long been intriguing because they self organize into spirals and that behavior can be analyzed. The form for the patterns that develop is highly dependent upon the form of the neighborhood. We extend this work to three dimensional cyclic cellular automata and observe self organization dependent upon the neighborhood type. This includes neighborhood types intermediate between Von Neumann and Moore neighborhoods. We also observe that the patterns include nested shells with the appropriate forms but that the nesting is far more complex than the spirals that occur in two dimensions.