海气耦合模式的优化方法研究

气候模式不断发展的同时，对高性能计算机提出了更高的要求，如何提高模式在现有计算机资源上的运行效率问题已越来越重要。文章介绍了利用编译器优化和手工优化技术对海气耦合模式进行优化试验，优化后模式运行效率提高60%，表明将这些优化方法应用到气候模式的改进工作中，可以达到较好的效果。     

非弹性反应谱计算的一个改进算法

本文就非弹性地震反应谱的计算问题（运动方程的形式，谱参量的选取，方程解算中恢复力模型上拐折点的处理和时间积分方法），给出了几点理论考虑，介绍了一个改进的算法。这一算法具有精度好和效率高的优点，这对做好结构抗震设计和其它地震工程问题中需要处理大量强震动数据的分析研究工作是有利的。文中还就双线型恢复力模型具体计算了2个例子（一个为屈服强化情形，另一个为理想弹塑性情形）。最后联系计算工作和计算结果，对非弹性反应谱计算中的其它有关事项做了补充讨论和说明。     

A reassessment of dynamic characteristics of the Quincy Bayview Bridge using output‐only identification techniques

A reassessment of the dynamic characteristics of the 542 m cable‐stayed Bayview Bridge in Quincy, Illinois, is presented using a newly developed output‐only system identification technique. The technique is applied to an extensive set of ambient vibration response data acquired from the bridge in 1987. Vertical, torsional and transverse modal frequencies of the deck are identified, and uncertainty in damping values are estimated using an automated procedure on several redundant measurements at four locations. Important practical implementation issues associated with the implementation of the procedure and selection of algorithm design parameters for stochastic subspace identification techniques are discussed. An overall mean and standard deviation of damping of 1.0±0.8% is estimated considering all identified vertical, torsional and transverse modes in the 0–2 Hz band. The mean damping for the fundamental vertical mode (0.37 Hz) is identified as 1.4±0.5%, and for the first coupled torsion–transverse mode (0.56 Hz) is identified as 1.1±0.8%. Variability in the damping estimates is shown to decrease as estimated modal RMS acceleration levels increase. Standard deviations on estimated damping range from 0.05% to 2%. The results are shown to be a substantial improvement in the evaluation of damping compared to earlier spectral analysis conducted on the same data set. Copyright © 2005 John Wiley & Sons, Ltd.     

A hybrid genetic—instance based learning algorithm for CE-QUAL-W2 calibration

This paper presents a calibration model for CE-QUAL-W2. CE-QUAL-W2 is a two-dimensional (2D) longitudinal/vertical hydrodynamic and water quality model for surface water bodies, modeling eutrophication processes such as temperature–nutrient–algae–dissolved oxygen–organic matter and sediment relationships. The proposed methodology is a combination of a ‘hurdle-race’ and a hybrid Genetic-k-Nearest Neighbor algorithm (GA-kNN). The ‘hurdle race’ is formulated for accepting–rejecting a proposed set of parameters during a CE-QUAL-W2 simulation; the k-Nearest Neighbor algorithm (kNN)—for approximating the objective function response surface; and the Genetic Algorithm (GA)—for linking both. The proposed methodology overcomes the high, non-applicable, computational efforts required if a conventional calibration search technique was used, while retaining the quality of the final calibration results. Base runs and sensitivity analysis are demonstrated on two example applications: a synthetic hypothetical example calibrated for temperature, serving for tuning the GA-kNN parameters; and the Lower Columbia Slough case study in Oregon US calibrated for temperature and dissolved oxygen. The GA-kNN algorithm was found to be robust and reliable, producing similar results to those of a pure GA, while reducing running times and computational efforts significantly, and adding additional insights and flexibilities to the calibration process.     

A Versatile Nonlinear Inversion to Interpret Gravity Anomaly Caused by a Simple Geometrical Structure

A geophysical interpretative method is proposed to depth, amplitude coefficient and geometrical shape factor determination of a buried structure from an observed gravity anomaly related to a cylinder or a sphere-like structure.The method is based on nonlinearly constrained mathematical modelling and also on stochastic optimization approaches. The proposed interpretative method first has been tested on theoretical synthetic models with different random errors at a certain depth, where a very close agreement has been observed between assumed and evaluated parameters. Subsequent field data have been considered for which the interpreted results by other methods are available for comparison. The agreement between the obtained results by the proposed technique and by other geophysical methods is good. A statistical analysis has been also carried out to demonstrate the accuracy and the precision of the suggested interpretative method.     

Studies on structural vibration control with MR dampers using μGA

A new approach to reducing the seismic response of spatial structures with magneto-theological （MR） dampers is presented in this paper. The Genetic Algorithm with small populations （μGA） is used to optimize the control for the MR dampers to reduce structural vibration, which is difficult to achieve using classical optimal control. The advantages of μGA are the use of global properties and that fewer conditions are required to obtain the optimal function. Numerical results demonstrate the effectiveness of the proposed method in reducing the seismic response of structures.     

一次逼近理论下边坡稳定的模糊随机数值分析

在协调元基础上,通过一次逼近理论,建立随机有限元模型,并通过模糊数学模型实现对边坡体工作状态的软化处理;借助于模糊随机数值方法对荆南长江干堤局部破坏失效进行了较为全面的研究。     

关于BP神经网络转换GPS高程的若干问题

BP神经网络用于GPS高程转换有着较高的精度,但也存在不少问题,如网络的隐含层和隐含层单元个数选取、参加学习的样本的质量如何影响仿真精度等。结合实例分析上述问题,得出一些结论。     

地震勘探中的时间-暴光声学

本文提出用于地下成像无源地震方法的分析,在该方法中应用环境地震噪声作为地下散射体的照明源。该成像算法能够以递归方式将新的数据融入到成像中,这使成像背景噪声随时间减少。在空间域不相干环境背景噪声的假设前提下推导出成像算法的点-扩展函数。点-扩展函数表征成像的分辨率,即接收排列长度和环境带宽的函数。     

副热带高压强度变化的模糊聚类诊断预测

采用模糊C均值聚类 (FCM)、遗传算法 (GA) 和模糊减法聚类 (FSC) 交叉融合、优势互补思想进行副热带高压影响因子的综合聚类分析和副热带高压指数的诊断预测。在统计分析的基础上, 通过选择若干与副热带高压指数关系密切的影响因子构成了高维特征空间, 进行了综合聚类分析, 实现了副热带高压指数的聚类判别和诊断预测。该文提出的综合聚类方法既可克服FCM/GA算法全局/局部寻优的不足, 又可客观确定聚类数目。试验结果表明, 该方法具有良好的分类效果, 判别结果与实况基本相符。