基于云模型的不确定性变量半定量化研究

文章针对复杂系统仿真中不确定性变量不能有效表示的关键问题,提出了一种基于群体决策和云模型的不确定性变量半定量化方法。首先综述了已有半定量化方法和云模型的基本概念;然后提出基于云模型的不确定性变量的半定量化方法,分别对群体专家给出的评估判断为具体值和区间值两种情况,给出了从群体专家判断到半定量化的云模型数字特征构建的理论和方法。

海上河流相储层应用地质模型计算储量的不确定性分析

影响海上河流相储层地质模型储量不确定性变量有构造、平面变差函数、储层属性与地震属性的相关性、束缚水饱和度、有效储层下限值、体积系数和油水界面等。分析了不确定性变量产生的根源,并以渤海Q油田为例,综合应用Monte-Carlo计算方法和随机建模技术,定量评价了不确定性变量对油田储量产生的影响,得到储量的概率累积分布曲线及悲观的(P90)、期望的(P50)和乐观的(P10)3个概率储量值,预测了储层储量存在的风险和潜力。

An Uncertain Programming Model for Land Use Structure Optimization to Promote Effectiveness of Land Use Planning

Land use structure optimization(LUSO) is an important issue for land use planning. In order for land use planning to have reasonable flexibility, uncertain optimization should be applied for LUSO. In this paper, the researcher first expounded the uncertainties of LUSO. Based on this, an interval programming model was developed, of which interval variables were to hold land use uncertainties. To solve the model, a heuristics based on Genetic Algorithm was designed according to Pareto Optimum principle with a confidence interval under given significance level to represent LUSO result. Proposed method was applied to a real case of Yangzhou, an eastern city in China. The following conclusions were reached. 1) Different forms of uncertainties ranged from certainty to indeterminacy lay in the five steps of LUSO, indicating necessary need of comprehensive approach to quantify them. 2) With regards to trade-offs of conflicted objectives and preferences to uncertainties, our proposed model displayed good ability of making planning decision process transparent, therefore providing an effective tool for flexible land use planning compiling. 3) Under uncertain conditions, land use planning effectiveness can be primarily enhanced by flexible management with reserved space to percept and hold uncertainties in advance.

钢悬链线立管强度可靠性计算研究

在钢悬链线立管分析中,材料性能、载荷参数、计算方法等都存在着大量不确定性。为考虑不确定性因素造成的影响,采用作用效应-抗力半随机过程构建可靠性模型,并采用极小化变换转化为静态可靠性问题。选用物理含义较为明确的屈服判定准则建立功能函数,通过单样本K-S检验对载荷随机过程的概率特性进行极值统计,提出载荷转化的方法以实现与目标可靠性指标的比对,并引入模型和主观不确定性随机变量。在此基础上采用改进的一次二阶矩法,对立管的强度可靠性进行了计算。结果表明此方法与利用系数方法能够相互印证,可以为立管的可靠性计算提供参考。

Discrete logistics network design model under interval hierarchical OD demand based on interval genetic algorithm

Aimed at the uncertain characteristics of discrete logistics network design,an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is presented.Under consideration of the system profit,the uncertain demand of logistics network is measured by interval variables and interval parameters,and an interval planning model of discrete logistics network is established.The risk coefficient and maximum constrained deviation are defined to realize the certain transformation of the model.By integrating interval algorithm and genetic algorithm,an interval hierarchical optimal genetic algorithm is proposed to solve the model.It is shown by a tested example that in the same scenario condition an interval solution[3275.3,3 603.7]can be obtained by the model and algorithm which is obviously better than the single precise optimal solution by stochastic or fuzzy algorithm,so it can be reflected that the model and algorithm have more stronger operability and the solution result has superiority to scenario decision.

烟草商业企业客户经理岗位素质评价方法探讨及应用

本文在前期建立的烟草商业企业客户经理岗位素质指标体系基础上,介绍了不确定性语言变量评价方法和步骤,并利用不确定性语言变量评价方法对客户经理岗位素质进行了评价,为下一步客户经理岗位档次划分提供了依据。

Making Business of a Revolutionary New Technology The Eckert-Mauchly Company, 1945-1951

The paper analyzes John Presper Eckert and John William Mauchly＇s endeavours to design, sell, and build the revolutionary new technology of the first-large and commercial computers. It discusses how Eckert and Mauchly＇s conceptualization of the computer grew out of their Electronic Numerical Integrator and Calculator （ENIAC） and Electronic Discrete Variable Automatic Computer （EDVAC） projects at University of Pennsylvania. They incorporated their own business to gain profit from production and attain the freedom needed to develop their revolutionary new computer technology through a series of small and separate computer projects with private and government customers. The paper approaches innovation as a chaotic process and uses uncertainty to conceptualize the basic relations between actors and organizations.

The need for alternative plant species interaction models

Aims The limitations of classical Lotka–Volterra models for analyzing and interpreting competitive interactions among plant species have become increasingly clear in recent years.Three of the problems that have been identified are(i)the absence of frequency-dependence,which is important for long-term coexistence of species,(ii)the need to take unmeasured(often unmeasurable)variables influencing individual performance into account(e.g.spatial variation in soil nutrients or pathogens)and(iii)the need to separate measurement error from biological variation.Methods We modified the classical Lotka–Volterra competition models to address these limitations.We fitted eight alternative models to pin-point cover data on Festuca ovina and Agrostis capillaris over 3 years in an herbaceous plant community in Denmark.A Bayesian modeling framework was used to ascertain whether the model amendments improve the performance of the models and increase their ability to predict community dynamics and to test hypotheses.Important Findings Inclusion of frequency-dependence and measurement error,but not unmeasured variables,improved model performance greatly.Our results emphasize the importance of comparing alternative models in quantitative studies of plant community dynamics.Only by considering possible alternative models can we identify the forces driving community assembly and change,and improve our ability to predict the behavior of plant communities.

Response-surface-based structural reliability analysis with random and interval mixed uncertainties

Traditional reliability analysis requires probability distributions of all the uncertain parameters.However,in many practical applications,the variation bounds can be only determined for the parameters with limited information.A complex hybrid reliability problem then will be caused when the random and interval variables coexist in a same structure.In this paper,by introducing the response surface technique,we develop a new hybrid reliability method to efficiently compute the interval of the failure probability of the structure due to the probability-interval hybrid uncertainty.The present method consists of a sequence of iterations.At each step,a response surface model is constructed for the limit-state function by using a quadratic polynomial and a modified axial experimental design method.An approximate hybrid reliability problem is created based on the response surface model,which is subsequently solved by an efficient decoupling approach.An updating strategy is suggested to improve the quality of the response surface and whereby ensure the reliability analysis precision.A computational procedure is then summarized for the whole iterations.Four numerical examples and also a practical application are provided to demonstrate the effectiveness of the present method.

Global warming, human-induced carbon emissions, and their uncertainties

In recent decades, there have been a number of debates on climate warming and its driving forces. Based on an extensive literature review, we suggest that （1） climate warming occurs with great uncertainty in the magnitude of the temperature increase; （2） both human activities and natural forces contribute to climate change, but their relative contributions are difficult to quan- tify; and （3） the dominant role of the increase in the atmospheric concentration of greenhouse gases （including CO2） in the global warming claimed by the Intergovernrnental Panel on Climate Change （IPCC） is questioned by the scientific communities because of large uncertainties in the mechanisms of natural factors and anthropogenic activities and in the sources of the increased atmospheric CO2 concentration. More efforts should be made in order to clarify these uncertainties.