A BENCHMARK EXERCISE ON FUZZY SET THEORY BASED EXPERT JUDGEMENT TECHNIQUE

Introduction　　In the areas of every level of probabilistic riskassessment and management in nuclear powerplants,the application of subjective expert' s judg-ments is broadly in demand.The behind reason isprobably thatthe assessmentis usually performed,based on the limited data due to the scarcity of op-erating experience and/or on the incompleteknowledge due to the complexity of phenomenaembedded in severe accidents[1] .In the literature,subjective expert' s judgment is also called expertjud…     

基于虚拟变量法的结构可靠度参数敏感性分析

在结构可靠度分析中,功能函数通常是强非线性的,并且随机变量之间往往存在相关性,这给基于一次二阶矩法原理的参数敏感性分析带来了困难。为此,提出了一种基于虚拟变量法的结构可靠度参数敏感性分析方法,推导了相关随机变量的敏感性计算公式,在计算可靠指标时无须求偏导,计算效率高。工程算例分析表明,在功能函数为非线性、变量之间相关的情况下,该计算方法是一种有效的结构可靠度敏感性分析方法。     

拇指屈伸运动诱发的脑电位的变化

观察各运动变量对拇指屈伸运动诱发脑电位的影响。当拇指运动时施以一定的抗屈负荷，随负荷的增加，脑电位中的Ｎ１波发生趋于提前；Ｎ２波与运动时的峰速度呈正相关；而且Ｐ２、Ｎ３波的发生则分别与屈曲运动的完成和伸张运动的起始有关。     

A probabilistic stationary speed–density relation based on Newell’s simplified car-following model

Probabilistic models describing macroscopic traffic flow have proven useful both in practice and in theory. In theoretical investigations of wide-scatter in flow–density data, the statistical features of flow density relations have played a central role. In real-time estimation and traffic forecasting applications, probabilistic extensions of macroscopic relations are widely used. However, how to obtain such relations, in a manner that results in physically reasonable behavior has not been addressed. This paper presents the derivation of probabilistic macroscopic traffic flow relations from Newell’s simplified car-following model. The probabilistic nature of the model allows for investigating the impact of driver heterogeneity on macroscopic relations of traffic flow. The physical features of the model are verified analytically and shown to produce behavior which is consistent with well-established traffic flow principles. An empirical investigation is carried out using trajectory data from the New Generation SIMulation (NGSIM) program and the model’s ability to reproduce real-world traffic data is validated.     

Demographic indicators of the relative need for artificial reefs in Florida

Abstract

Artificial reef development involves pfonning from a number of perspectives including biological, océanographie, engineering, and social. This article reviews previous studies and identifies demographic variables that affect the use of artificial reefs by recreational anglers. An index of relative demand was created employing eight components: number of coastal county resident boat anglers, nonresident boat anglers, tourist boat anglers, nonboat anglers, number of fishing clubs, number of charter/party boats, number of registered pleasure boats, and the rate of county population growth. By comparing the magnitude of the index to the number of existing artificial reefs off of Florida's 35 coastal counties, an estimate of relative need was graphically portrayed on a state map. Indian River county on the Atlantic coast and Hernando, Hillsborough, Pasco, Citrus, Levy, Lee, and Charlotte counties on the central Gulf coast are the areas with the greatest demand relative to existing reef supply.     

Transition to a cyclable city: Latent variables affecting bicycle commuting

An understanding of the key factors influencing bicycle commuting is essential for developing effective policies towards a cyclable city. This paper contributes to this line of research by proposing a methodology for including cycling-related indicators in mobility surveys based on the Theory of Planned Behaviour (TPB), and applying an exploratory factor analysis (EFA) to evaluate the structure of latent variables associated with bicycle commuting. The EFA identified six cycling latent variables: Lifestyle, Safety and comfort, Awareness, Direct disadvantages, Subjective norm, and Individual capabilities. These were complemented with a latent variable related to habit: Non-commuting cycling habit. Statistical differences and regression analysis were applied with the cycling latent variables. The study also includes the relationship between objective factors and bicycle commuting, which reveals minor associations. This methodology was applied to the “starter cycling city” of Vitoria-Gasteiz (Spain). The results confirm that in this context – in transition to a cyclable city – safety and comfort issues are not the main barriers for all commuters, although more progress needs to be made to normalise cycling. A set of customised policy initiatives is recommended in the light of the research findings, including marketing campaigns to encourage non-commuting cycling trips, bicycle measures to target social groups as opposed to individuals, bicycle-specific programs such as “Bike-to-work Days”, and cycling courses.     

双变量区间过滤法进行事故多发段判别

事故多发段的判别在安全管理中十分重要,判别方法很多,但一些方法难于操作或精度不够.笔者通过对大量事故样本的观察和分析,发现应用双变量区间过滤法,即变步长变区间过滤法进行事故多发段判别更符合样本特性并具有良好的精度.实例分析说明,该方法操作简单,同时有较高的精度.文章最后对应用双变量区间过滤法进行事故多发段的判别过程进行了总结.     

相关变量下失效概率的计算机模拟

岩土工程中基本变量大多数都为互相关，因此在计算其可靠度指标时要考虑其相关性。Ｍｏｎｔｅ－Ｃａｒｌｏ模拟法是求解失效概率Ｐｆ和可靠度指标β较为精确的方法，但只能对自相关的随机向量进行抽样；对于互相关的不同分布随机变量，则只能根据其联合概率分布求出其边缘分布和条件分布，化为独立的变量分布，然后在独立空间中抽样，但大多数情况下无法知其联合概率分布。     

On the Computation of Noether Normalization

This paper considered the Noether normalization of a finitely generated algebra over an algebraically closed field. It gives a necessary and sufficient condition as well as an algorithm for the identification of those algebraically independent variables, then uses these elements to construct the Noether normalization of this algebra.     

A new generalized heterogeneous data model (GHDM) to jointly model mixed types of dependent variables

This paper formulates a generalized heterogeneous data model (GHDM) that jointly handles mixed types of dependent variables—including multiple nominal outcomes, multiple ordinal variables, and multiple count variables, as well as multiple continuous variables—by representing the covariance relationships among them through a reduced number of latent factors. Sufficiency conditions for identification of the GHDM parameters are presented. The maximum approximate composite marginal likelihood (MACML) method is proposed to estimate this jointly mixed model system. This estimation method provides computational time advantages since the dimensionality of integration in the likelihood function is independent of the number of latent factors. The study undertakes a simulation experiment within the virtual context of integrating residential location choice and travel behavior to evaluate the ability of the MACML approach to recover parameters. The simulation results show that the MACML approach effectively recovers underlying parameters, and also that ignoring the multi-dimensional nature of the relationship among mixed types of dependent variables can lead not only to inconsistent parameter estimation, but also have important implications for policy analysis.