色散方程两层绝对稳定的实心隐格式

利用组合差商法对色散方程ur=auxxx的初边值问题构造了一组带参数的2层4点实心隐式差分格式，其截断误差为0（τ^2＋h^4），绝对稳定．这是一组高精度、高稳定的差分格式．     

平板在组合载荷作用下的极限强度预报的一种简化解析法

船体平板强度在船舶结构极限强度分析中起到十分重要的作用。最近几年，一些作者提出了计算平板极限强度的一种简化解析方法。但绝大部分的研究只考虑了平板纵向受压这一种简单载荷的情况。在我们成功地解决了三向组合载荷(纵、横压缩和垂向均布压力)的基础上，在本文中，我们又进一步将此方法推广到包含面内剪力在内的所有组合载荷分量均存在的一般情况。通过与一些规范公式的比较表明，本文所推导的公式是可以比较精确地预报平板在一般组合载荷作用下的极限强度。这一工作一方面可以为规范中的一些经验公式提供理论依据，另一方面也许可以提供比经验公式更好的外插能力。为了简化使用本文的方法，本文也在大量参数系列计算的基础上给出了一个回归的经验公式。     

交通分布-交通分配组合模型研究

在交通规划实践中，交通分布和交通分配问题作为“四阶段预测模型”各自独立，尽管两个问题紧密相关．因此，有必要建立交通分布-交通分配组合模型，来反映这种反馈．文中介绍了Evans模型，并说明了逐次平均法求解模型的步骤，最后用算例说明了具体算法．这种方法完全可以用Microsoft Excel计算，计算方法简单，可以为组合模型的求解提供新的思路．     

Modeling techniques for periodic vehicle routing problems

This paper presents a continuous approximation model for the period vehicle routing problem with service choice (PVRP-SC). The PVRP-SC is a variant of the period vehicle routing problem in which the visit frequency to nodes is a decision of the model. This variation can result in more efficient vehicle tours and/or greater service benefit to customers. We present a continuous approximation model to facilitate strategic and tactical planning of periodic distribution systems and evaluate the value of service choice. Further, results from the continuous model can provide guidelines for constructing solutions to the discrete PVRP-SC.     

基础沉降的组合预测法

通过对基础沉降的发生过程、特点及灰色Verhulst模型特点的分析,提出可以根据施工过程中的观测资料,运用基于BP神经网络的组合预测模型对不同时刻的基础沉降进行预测;首先分别利用灰色Verhulst模型和BP神经网络模型对基础沉降进行估算,然后利用人工神经网络中的BP神经网络对采用前2种模型所得的结果进行组合预测。计算实例表明,使用该组合预测方法所得到的预测结果比单独使用灰色Verhulst模型或BP神经网络模型所得到的预测结果的总体误差要小,因而该方法是可行的、有效的;可以运用到实际工程中。     

Preparing highway emissions inventories for urban scale modeling: A case study in Philadelphia

Highway emissions represent a major source of many pollutants. Use of local data to model these emissions can have a large impact on the magnitude and distribution of emissions predicted and can significantly improve the accuracy of local scale air quality modeling assessments. This paper provides a comparison of top–down and bottom–up approaches for developing emission inventories for modeling in one urban area, Philadelphia, in calendar year 1999. A bottom–up approach relies on combining motor vehicle emission factors and vehicle activity data from a travel demand model estimated at the road link level to generate hourly emissions data. This approach can result in better estimates of levels and spatial distribution of on-road motor vehicle emissions than a top–down approach that relies on more aggregated information and default modeling inputs.     

软件过程改进的动态建模仿真

给出了一种软件过程改进的动态集成框架，将传统的评估模型与软件过程的动态仿真模型结合起来，为软件过程改进和决策提供定性和定量的评估，并依照能力成熟度模型获得更高的软件开发过程能力。     

Future aspects in marine ecosystem modelling

Existing ecosystem models are briefly presented and summarised. The problem of coupling physical and biological models as well as aspects of prediction and predictability are discussed. The general perception that marine ecosystems are inherently unpredictable due to non-linearity becomes questionable if the response of climate variability in marine ecosystems is analysed. Many authors have shown correlations between climate variability and the variability of abundance or biomass of marine organisms such as phytoplankton, zooplankton, benthos or fish recruitment in different parts of the world ocean. In the northern hemisphere, certain species show a linear response to climate variability mainly during winter and spring. However, the underlying mechanisms are not well understood. Often, a phase lag can be observed between climate variability and the reaction of organisms. The identification of a plausible mediator between climate and biology is difficult, since all possible physicochemical mechanisms having a direct or indirect influence on the variability of abundance or biomass of marine organisms have to be considered as mediator.The understanding of the reason of the phase lag, which possibly implies a “biological memory”, and the identification of all possible mediators are necessary to predict the response of marine organisms to climate variability. The identification of mediators will result in an improvement of coupled models, a deeper understanding of physical–biological interaction and the improvement of predictive capability of marine ecosystem models.     

The principles of calibrating traffic microsimulation models

Traffic microsimulation models normally include a large number of parameters that must be calibrated before the model can be used as a tool for prediction. A wave of methodologies for calibrating such models has been recently proposed in the literature, but there have been no attempts to identify general calibration principles based on their collective experience. The current paper attempts to guide traffic analysts through the basic requirements of the calibration of microsimulation models. Among the issues discussed here are underlying assumptions of the calibration process, the scope of the calibration problem, formulation and automation, measuring goodness-of-fit, and the need for repeated model runs.