基于自忆性原理的多变量MGM(1,m)耦合系统模型构建及应用

针对小样本条件下具有相互制约关系的多变量系统,本文提出了一种新颖的多变量MGM(1,m)自忆性耦合系统模型,用来统一描述系统各变量间关系并且提高其建模精度。该模型通过有机耦合动力系统自忆性原理与传统MGM(1,m)模型,综合了两者各自的优势。系统的自忆性方程包含多个时次初始场而不仅是单个时次初始场,从而克服了传统灰色预测模型对初值比较敏感的弱点。对基坑变形预测的实例研究结果表明,所构建模型能够充分利用系统的多个历史时次资料,可以紧密捕捉系统演化趋势,模拟预测精度显著高于传统多变量MGM(1,m)模型。研究结果表明,新模型丰富和完善了灰色预测理论,值得推广应用于其他类似的多变量系统。     

基于区间灰作用量的GM(1,1)均值差分模型解的非唯一性研究

GM(1,1)是结构信息不完全的灰色预测模型，但当前其模拟及预测结果的实数形式不满足灰色理论解的非唯一性原理。文章从GM(1,1)网络模型出发，分析了灰作用量的背景与内涵，还原了影响因素不确定条件下灰作用量的区间灰数形式，构建了具有非唯一解的新型GM(1,1)均值差分模型。新模型具有更加完善的体系结构，同时能实现对传统 GM(1,1)均值差分模型的完全兼容。应用新模型对我国电力能源消费量进行建模，结果显示其建模结果的合理性优于传统 GM(1,1)模型。本研究成果对丰富灰色预测模型理论框架、完善灰色预测模型结构体系具有积极意义。     

面向灾害应急物资需求的灰色异构数据预测建模方法

多源信息集结对提高自然灾害环境下统计数据可信度具有重要作用,但信息渠道的多源性极易导致集结信息数据类型不一致、不兼容,形成灰色异构数据序列。本文应用灰色系统建模技术对灰色异构数据预测建模方法展开研究,首先,基于"核"和"灰度"对灰色异构数据进行规范化处理;然后,建立灰色异构数据"核"序列的DGM(1,1)模型,并以"核"为基础,根据灰度不减公理,以灰色异构数据序列中最大灰度值所对应的信息域作为预测结果之信息域,推导并构建了灰色异构数据预测模型;最后,将该模型应用于某地震帐篷需求量的预测。本文研究成果将传统灰色模拟及预测模型建模对象从"同质数据"拓展至"异构数据",对丰富与完善灰色模拟及预测模型理论体系,提高自然灾害救援效率具有积极意义。     

基于区间灰数列的GM(1,1) 模型(GMBIGN(1,1))研究

GM(1,1)模型在灰系统的理论与应用研究中占有十分重要的地位,然而目前的GM(1,1)模型只能适用于对白化数表征的数列进行预测,而对于现实中存在的区间灰数表示的数列却无能为力.本文运用有关标准区间灰数的最新研究成果,构建了基于区间灰数表征的GM(1,1)模型GMBIGN(1,1)(GM(1,1)Based on Interval GreyNumber,GMBIGN(1,1)),并给出了其解析解.在此基础之上,本文以某地区某种能源价格区间变动情况这一现实经济问题为背景,建立了该地区某种能源价格区间变动的GMBIGN(1,1)模型,并对其进行了仿真与误差分析,效果良好.     

估计灰色Verhulst模型参数的LS-SVM方法及应用

估计灰色Verhulst模型中的参数通常采用最小二乘法，这种基于大样本理论的经验风险最小化方法无法保证小样本预测下模型的推广性能.为提高灰色Verhulst模型的预测精度，本文提出了基于LS-SVM算法估计模型参数的方法.首先根据Verhulst灰色差分方程的特点，通过构造以背景值序列和原始序列为训练样本的LS-SVM模型，将一维样本空间里的Verhulst模型转化为一个二维特征空间里的LS-SVM模型，进而将Verhulst模型的灰参数的估计问题转化为一个LS-SVM模型的回归系数估计问题.然后通过核函数构造法，结合模型特点合理构造了LS-SVM模型的核函数，基于LS-SVM算法求解回归系数，进而得到Verhulst模型的参数估计.实验结果表明该方法是可行的有效的，可保证Verhulst模型具有良好推广性，相比于传统参数估计方法本文预测精度更高.     

具有灰指数律数据序列的建模方法研究

通过对灰色系统理论建模机理的分析,建立了对于具有灰指数律的数据序列的EGM模型,通过模拟、试验验证了该模型对于具有灰指数律数据序列的模拟值与预测精度都高于GM(1,1)模型,表明了该模型对具有灰指数律数据序列的有效性与适用性.     

基于驱动因素控制的线性时变参数DLDGM(1,N)模型

针对传统GM(1,N)模型未考虑参数随时间变化的动态特征及未明确驱动因素作用机制的问题,首先引入线性时变参数以及驱动因素控制函数,构建基于驱动因素控制的线性时变参数DLDGM(1,N)模型,论证DGM(1,1)、NDGM(1,1)、TDGM(1,1)、DGM(1,N)、DCDGM(1,N)模型均是该模型在不同参数取值下的特殊形式;然后基于白化信息充分和匮乏的两种情况,给出驱动因素控制参数的识别方法;最后应用所提模型对河南省粮食产量进行预测,验证模型的有效性和实用性。     

基于白化权函数的区间灰数关联度模型

根据区间灰数空间映射思想,引入白化权函数来表征区间灰数的分布信息。定义灰形和灰心分别来描述白化权函数与区间灰数围成的封闭几何图形及其几何重心;定义灰圆和灰径分别来表示以灰心为圆心且与灰形具有相同面积的标准圆及其半径。在此基础上,以灰心序列的横、纵坐标序列为对象,以灰径的离差为权重,依照邓氏关联度原理构造了一个基于白化权函数的区间灰数关联度模型。并针对一种最为典型的白化权函数,具体导出了区间灰数关联度的计算公式。最后,通过一个供应商选择的实例验证了模型的科学性和可行性。基于白化权函数的区间灰数关联度在资源勘探、机器故障诊断、产品品质评价及供应商选择等方面有着广泛的应用前景。     

季节性数据特征驱动的电子废弃物回收规模分解集成预测建模研究

电子废弃物回收规模预测是政府制定循环经济发展规划和有关补贴政策、企业进行资源回收价值评估和产能优化的基础。本文考虑电子废弃物回收规模季度数据的季节性数据特征可能导致传统单模型预测误差偏大、预测结果不稳定等问题，基于“分解-集成”的思想提出了季节性数据特征驱动的电子废弃物回收规模预测CH-X12/STL-X框架。首先，基于Canova-Hansen(CH)检验对电子废弃物回收规模时间序列的季节性数据特征进行识别，继而对适于进行季节性分解的时间序列采用X12乘法模型或时间序列季节性分解(Seasonal-trend Decomposition Procedure Based on Loess，STL)模型实现季节性分量提取。然后，采用Holt-Winters模型对获得的季节性分量进行预测，并以支持向量回归模型(Support Vector Regression，SVR)预测分解获得的其他分量。最后，通过对各个分量预测结果的线性求和以得到最终的预测结果。实证结果表明，提出CH-X12/STL-X预测框架能够较好地满足不同季节性数据特征驱动的时间序列预测建模需求，且较传统单模型(Holt-Winters模型、季节性差分自回归滑动平均模型、SVR模型)在预测性能上表现良好且稳定。     

基于EEMD-LSTM的农产品价格短期预测模型研究

本文将集成经验模态分解(EEMD)方法与长短期记忆网络(LSTM)相结合，构建了一个端到端的农产品价格短期预测模型。首先，对原始价格信号进行EEMD分解，得到若干IMF子序列和一个残差序列；然后，运用Fine-to-coarse高低频重构方法对IMF子序列进行高频—低频重构；最后将原始价格序列、高频项、低频项和残差趋势项作为特征，输入到LSTM网络进行训练得到预测模型。本文以广州市江南农副产品市场的富士苹果日价格为例进行实证分析，结果表明，本文提出的EEMD-LSTM模型在农产品价格短期预测问题上具有一定的性能优势。     

股权融资下企业市场竞争策略选择的模型研究

企业市场竞争策略的制定不仅应考虑竞争双方运营层面的因素,还应重视其资本运作带来的影响。本文构建了零售商采取股权融资进行市场开拓的市场竞争模型,探讨其市场竞争策略选择及其影响因素。研究发现：零售商的市场竞争策略取决于其成长性和市场开拓的外部性;提高成长性或外部性均能促进企业的股权融资,而企业原股东的委托代理行为会抑制股权融资,并影响其市场开拓决策,但不会定性改变企业的价格竞争策略。此外,当市场开拓呈现负外部性时,竞争者应采取相应措施以避免掉入“融资企业成长性陷阱”。     

灰霾环境下能源效率测算与节能减排潜力分析-基于多非期望产出的NH-DEA模型

考虑到现有能源效率测算未把灰霾作为环境约束这一问题,基于非参数前沿构建了不可分的混合测度DEA 模型,将致霾污染物SO₂、NOx、CO₂和烟（粉）尘作为非期望产出,对各省份2010-2013年灰霾环境约束下的能源效率进行了更加科学的测算,结果发现：我国省际能源效率差异比较大;东部平均能源效率最高,中部次之,西部最差;我国整体的能源效率为0.63。通过Tobit 模型对能源效率的影响因素进行分析,发现能源禀赋、产业结构、政府影响力和能源效率呈显著的负相关关系,技术进步和能源效率呈显著正相关关系,各因素对我国区域间的影响程度存在差异。在节能减排潜力方面,我国各省份的能源节约潜力和致霾污染物减排潜力都很大。这些结果有助于制定能源节约和灰霾治理规划。     

Health Effects Caused by Primary Fine Particulate Matter (PM2.5) Emitted from Buses in the Helsinki Metropolitan Area, Finland

Fine particle (PM(2.5)) emissions from traffic have been associated with premature mortality. The current work compares PM(2.5)-induced mortality in alternative public bus transportation strategies as being considered by the Helsinki Metropolitan Area Council, Finland. The current bus fleet and transportation volume is compared to four alternative hypothetical bus fleet strategies for the year 2020: (1) the current bus fleet for 2020 traffic volume, (2) modern diesel buses without particle traps, (3) diesel buses with particle traps, and (4) buses using natural gas engines. The average population PM(2.5) exposure level attributable to the bus emissions was determined for the 1996-1997 situation using PM(2.5) exposure measurements including elemental composition from the EXPOLIS-Helsinki study and similar element-based source apportionment of ambient PM(2.5) concentrations observed in the ULTRA study. Average population exposure to particles originating from the bus traffic in the year 2020 is assumed to be proportional to the bus emissions in each strategy. Associated mortality was calculated using dose-response relationships from two large cohort studies on PM(2.5) mortality from the United States. Estimated number of deaths per year (90% confidence intervals in parenthesis) associated with primary PM(2.5) emissions from buses in Helsinki Metropolitan Area in 2020 were 18 (0-55), 9 (0-27), 4 (0-14), and 3 (0-8) for the strategies 1-4, respectively. The relative differences in the associated mortalities for the alternative strategies are substantial, but the number of deaths in the lowest alternative, the gas buses, is only marginally lower than what would be achieved by diesel engines equipped with particle trap technology. The dose-response relationship and the emission factors were identified as the main sources of uncertainty in the model.     

Intake Fraction Variability Between Air Pollution Emission Sources Inside an Urban Area

The cost‐effective mitigation of adverse health effects caused by air pollution requires information on the contribution of different emission sources to exposure. In urban areas the exposure potential of different sources may vary significantly depending on emission height, population density, and other factors. In this study, we quantified this intraurban variability by predicting intake fraction (iF) for 3,066 emission sources in Warsaw, Poland. iF describes the fraction of the pollutant that is inhaled by people in the study area. We considered the following seven pollutants: particulate matter (PM), nitrogen oxides (NO_x), sulfur dioxide (SO₂), benzo[a] pyrene (BaP), nickel (Ni), cadmium (Cd), and lead (Pb). Emissions for these pollutants were grouped into four emission source categories (Mobile, Area, High Point, and Other Point sources). The dispersion of the pollutants was predicted with the CALPUFF dispersion model using the year 2005 emission rate data and meteorological records. The resulting annual average concentrations were combined with population data to predict the contribution of each individual source to population exposure. The iFs for different pollutant‐source category combinations varied between 51 per million (PM from Mobile sources) and 0.013 per million (sulfate PM from High Point sources). The intraurban iF variability for Mobile sources primary PM emission was from 4 per million to 100 per million with the emission‐weighted iF of 44 per million. These results propose that exposure due to intraurban air pollution emissions could be decreased more effectively by specifically targeting sources with high exposure potency rather than all sources.     

基于Metacost的客户信用评估半监督异构集成模型研究

针对现实中信用评估存在的问题,本研究将元代价敏感学习、半监督学习和异构集成等技术结合,提出了基于Metacost的客户信用评估半监督异构集成模型(Metacost based semi-supervised heterogeneous ensemble model, Meta-Semi-HE)。该模型主要包括三个阶段：1)用Metacost方法修改初始有标签训练集得到Lm;2)在Lm上通过AdaBoost方法训练N个异构分类器hi(i = 1,…, N),用伴随分类器组合Hi选择性标记无标签数据集的样本,并将其添加到Lm中,用新的Lm重新训练N个异构分类器。重复这一步骤,不断提高分类器性能,直至满足终止条件;3)用最终的N个异构分类器对测试集样本分类。在6个客户信用评估数据集上进行实证分析,结果表明,与已有的3种半监督集成模型和2种监督式集成模型相比,本研究提出的模型具有更好的客户信用评估性能。     

基于多种污染物损害视角的地方政府间环境规制合作策略研究

考虑多种(非累积性和累积性)污染物对环境造成不同损害的前提下,首先基于Stackelberg博弈分析占主导的地方政府和跟随的工业企业各自的动态决策过程,确定工业企业的最优污染物排放量;随后运用最优控制理论构建两个相邻地区在非合作和合作博弈下关于跨界污染最优控制的博弈模型,分析地方政府的环境治理策略,包括最优的环境保护税、污染治理投资,探讨污染物存量的动态变化情况,并对此两种博弈结构进行了比较分析。理论及仿真分析表明：无论地区间是非合作还是合作博弈,工业企业的最优污染物排放量与其污染物减排比例的相关性不确定;每个地区的最优环境保护税与污染物减排比例呈正相关。但合作博弈下,每个地区均会考虑其非累积性污染物排放对其相邻地区造成的损害;每个地区均会增加污染治理投资;所有地区的总收益高于非合作博弈下,且高出部分(合作剩余)受累积性污染物的损害以及非累积性污染物对相邻地区损害的影响,但是与非累积性污染物对本地区的损害无关。     

Estimates of the Health Risk Reductions Associated with Attainment of Alternative Particulate Matter Standards in Two U.S. Cities

As part of its periodic re-evaluation of particulate matter (PM) standards, the U.S. Environmental Protection Agency estimated the health risk reductions associated with attainment of alternative PM standards in two locations in the United States with relatively complete air quality data: Philadelphia and Los Angeles. PM standards at the time of the analysis were defined for particles of aerodynamic diameter less than or equal to 10 microm, denoted as PM-10. The risk analyses estimated the risk reductions that would be associated with changing from attainment of the PM-10 standards then in place to attainment of alternative standards using an indicator measuring fine particles, defined as those particles of aerodynamic diameter less than or equal to 2.5 microm and denoted as PM-2.5. Annual average PM-2.5 standards of 12.5, 15, and 20 microg/m3 were considered in various combinations with daily PM-2.5 standards of 50 and 65 microg/m3. Attainment of a standard or set of standards was simulated by a proportional rollback of "as is" daily PM concentrations to daily PM concentrations that would just meet the standard(s). The predicted reductions in the incidence of health effects varied from zero, for those alternative standards already being met, to substantial reductions of over 88% of all PM-associated incidence (e.g., in mortality associated with long-term exposures in Los Angeles, under attainment of an annual standard of 12.5 microg/m3). Sensitivity analyses and integrated uncertainty analyses assessed the multiple-source uncertainty surrounding estimates of risk reduction.     

“Do as I Do and Not as I Say”: Exploring Price‐Oriented Maverick Buying During Supplier Selection

This article empirically examines the occurrence of price‐oriented maverick buying (MB) during supplier selection, in a direct purchasing process context. Drawing on agency theory, maverick buying, and total cost of ownership (TCO) literature, the statistically significant existence of price‐oriented MB is investigated and the purchasing manager (PM)‐related factors that influence such noncompliant behavior are determined. A discrete choice experiment is designed to simulate a TCO‐based supplier selection process in which an established purchasing framework agreement stipulates PMs not necessarily be price‐oriented (i.e., select suppliers primarily based on lowest price), and then models PM choice behavior in the supplier selection process (SSP), utilizing a conditional logit model (CLM) to determine PM compliance to the established purchasing framework agreement and identify if price‐oriented MB exists. Statistical tests utilizing comprehensive primary and secondary data are then conducted to determine if correlational relationships exist between PM‐related factors and PM price‐orientation. Results indicate that three PM‐related factors bear a significant correlational relationship to PM price‐orientation.     

Exposure Assessment: Methods of Analysis for Environmental Carcinogens1

Human populations are exposed to environmental carcinogens in both indoor and outdoor atmospheres. Recent studies indicate that pollutant concentrations are generally higher in indoor atmospheres than in outdoor. Environmental pollutants that occur in indoor air from a variety of sources include radon, asbestos, organic and inorganic compounds, and certain particles (e.g., tobacco smoke). Some of the gases or vapors are adsorbed on suspended particulate matter, whereas others exist entirely in the gas phase or are distributed between the latter and a particle-bound state. Because of differences in chemical and physical properties, each class of carcinogens generally requires different sampling and analytical methods. In addition, a single indoor environment may contain a wide variety of air pollutants from different sources. Unfortunately, no single best approach currently exists for the quantitative determination of such complex mixtures and, for practical reasons, only the more toxic or the more abundant pollutants are usually measured. This paper summarizes the currently available monitoring methods for selected environmental pollutants found in indoor atmospheres. In addition, some possible sources for those pollutants are identified.