Improved generalized Fourier amplitude sensitivity test (FAST) for model assessment

The Fourier amplitude sensitivity test (FAST) can be used to calculate the relative variance contribution of model input parameters to the variance of predictions made with functional models. It is widely used in the analyses of complicated process modeling systems. This study provides an improved transformation procedure of the Fourier amplitude sensitivity test (FAST) for non-uniform distributions that can be used to represent the input parameters. Here it is proposed that the cumulative probability be used instead of probability density when transforming non-uniform distributions for FAST. This improvement will increase the accuracy of transformation by reducing errors, and makes the transformation more convenient to be used in practice. In an evaluation of the procedure, the improved procedure was demonstrated to have very high accuracy in comparison to the procedure that is currently widely in use.     

论我国农村居民收支的不确定性与非持续消费

农村居民的收入与支出的不确定性是客观存在的,这种不确定性是我国农村居民非持续消费的重要原因。非持续消费即有宏观层次的含义,又有微观层面的含义,两种非持续消费相互影响,它们不利于农村居民生活质量的提高和人的全面发展,也不利于国民经济的良性循环。     

论不确定性会计计量的影响因素

文章分析了传统财务会计计量模式对不确定性会计计量的局限性,并主要从不确定性经济业务特性、计量属性特性和会计理论方面论述了影响不确定性会计计量模式的选择因素。     

Node deletion sequences in influence diagrams using genetic algorithms

Influence diagrams are powerful tools for representing and solving complex inference and decision-making problems under uncertainty. They are directed acyclic graphs with nodes and arcs that have a precise meaning. The algorithm for evaluating an influence diagram deletes nodes from the graph in a particular order given by the position of each node and its arcs with respect to the value node. In many cases, however, there is more than one possible node deletion sequence. They all lead to the optimal solution of the problem, but may involve different computational efforts, which is a primary issue when facing real-size models. Finding the optimal deletion sequence is a NP-hard problem. The proposals given in the literature have proven to require complex transformations of the influence diagram. In this paper, we present a genetic algorithm-based approach, which merely has to be added to the influence diagram evaluation algorithm we use, and whose codification is straightforward. The experiments, varying parameters like crossover and mutation operators, population sizes and mutation rates, are analysed statistically, showing favourable results over existing heuristics.     

论不确定性数学在教育研究中的应用

科学发展的数学化、定量化趋势,要求我们寻找适宜的数学方法去描述教育现象和规律。不确定性数学是综合处理不确定性信息的数学理论和方法。模糊数学、灰色系统理论对于教育研究工作具有方法和方法论的作用。     

The impact of component commonality in an assemble-to-order environment under supply and demand uncertainty

A material requirements planning simulator with a two-level bill-of-material is used to study the impact of introducing component commonality into an assemble-to-order environment when demand is subject to random variations, and component procurement orders experience random delays. By using simulated data, our ANOVA results show that component commonality significantly interacts with existence of demand and supply chain uncertainties, and benefits of component commonality are most pronounced when both uncertainties exist.     

中国城市化的礼物--城市礼物回收店的社会观察

在当今城市社会人与人之间普遍流通的礼物并非从来如此,而是其自身有社会变化的特性相伴随。礼品回收店视角、通过梳理新中国以后各阶段城市礼物的特征探视社会连接的方式与性质。认为,始于知青下放、被体制改革强化的生活不确定性是中国城市礼物流动背后的逻辑。并且,本文试图借此为礼物作为人类学经久不衰的话题、为面临急剧分化与分层的社会开具药方的理论界提供一个另类视角。     

A Probabilistic Arsenic Exposure Assessment for Children Who Contact Chromated Copper Arsenate (CCA)-Treated Playsets and Decks, Part 2: Sensitivity and Uncertainty Analyses

A probabilistic model (SHEDS-Wood) was developed to examine children's exposure and dose to chromated copper arsenate (CCA)-treated wood, as described in Part 1 of this two-part article. This Part 2 article discusses sensitivity and uncertainty analyses conducted to assess the key model inputs and areas of needed research for children's exposure to CCA-treated playsets and decks. The following types of analyses were conducted: (1) sensitivity analyses using a percentile scaling approach and multiple stepwise regression; and (2) uncertainty analyses using the bootstrap and two-stage Monte Carlo techniques. The five most important variables, based on both sensitivity and uncertainty analyses, were: wood surface residue-to-skin transfer efficiency; wood surface residue levels; fraction of hand surface area mouthed per mouthing event; average fraction of nonresidential outdoor time a child plays on/around CCA-treated public playsets; and frequency of hand washing. In general, there was a factor of 8 for the 5th and 95th percentiles and a factor of 4 for the 50th percentile in the uncertainty of predicted population dose estimates due to parameter uncertainty. Data were available for most of the key model inputs identified with sensitivity and uncertainty analyses; however, there were few or no data for some key inputs. To evaluate and improve the accuracy of model results, future measurement studies should obtain longitudinal time-activity diary information on children, spatial and temporal measurements of residue and soil concentrations on or near CCA-treated playsets and decks, and key exposure factors. Future studies should also address other sources of uncertainty in addition to parameter uncertainty, such as scenario and model uncertainty.     

金融市场中的不确定性与其风险测度技术

介绍了金融市场上三种不确定性的形成机理，探讨了精算学中对于不确定性金融后果进行量化管理的风险管理技术，特别是金融风险测度技术所应遵循的计量原则，并就不同风险系统下的风险管理技术选择问题进行了深入系统的研究，给出了相应的结果。