鸭绿江口及邻近浅海碎屑矿物特征与物源辨识

通过分析鸭绿江口及邻近浅海表层沉积物的碎屑矿物特征,讨论了表层沉积物中主要碎屑矿物的沿程变化、指示性矿物、特征指数方面的差异及其示踪意义。研究结果表明:鸭绿江口与邻近浅海的沉积物可能来自于不同的物源区;西水道的沉积保留了较多的鸭绿江历史沉积的特点;中水道沉积与现代河流相近;辽东浅滩的沉积物质来源以河流为主,兼有来自浅海的物质。     

中低孔渗储层岩石弹性参数的流体敏感性研究(英文)

本文从WXS凹陷中低孔渗储层岩石声波实验出发,以岩样的纵横波速度和密度为基础数据,求取出一系列的弹性参数,包括纵横波波速比、纵波波阻抗、横波波阻抗、泊松比、拉梅常数、剪切模量、体积模量、杨氏模量,等等。在前人的孔隙流体识别究基础上,综合相关理论和实验分析,构建了一个新的流体识别因子F。以饱和流体岩石弹性参数及其组合参数的相对变化量Ag/w和Ao/w为定量指标,评价各流体识别因子的流体识别效果,并采用交会图技术进行了验证。新流体敏感因子在传统较难分辨的孔隙流体"水"和"油"的区别上具有良好效果,有利于提高中低孔渗储层流体识别的成功率。     

业主对不平衡投标报价风险的灰聚类识别方法研究

在招投标阶段,大中型工程项目的业主要识别的风险可能因素很多,投标单位的不平衡报价就是其中的一个重要因素。一般情况下,投标单位的不平衡报价对业主来讲具有灰色信息的特点,采用灰色系统理论,考虑到报价信息对招标方、业主不完全、关系不完全明确的特点,提出了基于灰聚类的不平衡报价风险定量识别办法,克服了在大型工程中没有大样本统计数据的不足。     

具有逆辨识结构的模糊神经网络控制及其应用

该文提出一种新型模糊神经网络结构及算法。在这种控制方案中,采用三层模糊神经网络控制器和神经网络逆辨识控制器相结合的结构。计算机仿真研究和实际应用表明,采用新型模糊神经网络控制方法,对大滞后非线性系统的控制是有效的。     

基于新型联想记忆神经网络的非线性系统辨识

Hopfield网络模型具有联想存储器功能,但对系统辨识不适用。具有动态记忆功能的Elman神经网络的泛化能力比较低。该文提出了一种新型联想记忆神经网络结构和学习算法,通过引入联想记忆衰减因子,提高了对非线性系统的辨识能力。通过与Elman动态神经网络辨识方法的仿真比较,说明联想记忆神经网络辨识方法具有很好的动态辨识能力和泛化能力。     

基于MPSO的RBF耦合算法的桩基动测参数辨识

变异粒子群优化算法（MPSO）是一种基于群体智能的改进全局优化技术,其优势在于减小陷入局部极值的机率,增加全局搜索能力。将变异粒子群算法与径向基函数（RBF）神经网络结构进行结合,建立了变异粒子群神经网络（MPSO-RBF）耦合算法,充分发挥了MPSO算法的全局寻优能力和RBF算法的局部搜索优势。数值计算结果表明,所建立的方法能够对桩基动测进行多参数的识别和非线性优化问题的求解,具有良好全局收敛能力,是一种行之有效的智能算法。     

Seismic analysis of two‐way asymmetric building systems under bi‐directional seismic ground motions

An approximation approach of seismic analysis of two‐way asymmetric building systems under bi‐directional seismic ground motions is proposed. The procedures of uncoupled modal response history analysis (UMRHA) are extended to two‐way asymmetric buildings simultaneously excited by two horizontal components of ground motion. Constructing the relationships of two‐way base shears versus two‐way roof translations and base torque versus roof rotation in ADRS format for a two‐way asymmetric building, each modal pushover curve bifurcates into three curves in an inelastic state. A three‐degree‐of‐freedom (3DOF) modal stick is developed to simulate the modal pushover curve with the stated bifurcating characteristic. It requires the calculation of the synthetic earthquake and angle β. It is confirmed that the 3DOF modal stick is consistent with single‐degree‐of‐freedom modal stick in an elastic state. A two‐way asymmetric three‐story building was analyzed by UMRHA procedure incorporating the proposed 3DOF modal sticks. The analytical results are compared with those obtained from nonlinear response history analysis. It is shown that the 3DOF modal sticks are more rational and effective in dealing with the assessment of two‐way asymmetric building systems under two‐directional seismic ground motions. Copyright © 2007 John Wiley & Sons, Ltd.     

Output‐only structural identification in time domain: Numerical and experimental studies

By identifying changes in stiffness parameters, structural damage can be detected and monitored. Although considerable progress has been made in this research area, many challenges remain in achieving robust structural identification based on incomplete and noisy measurement signals. The identification task is made even more difficult if measurement of input force is to be eliminated. To this end, an output‐only structural identification strategy is proposed to identify unknown stiffness and damping parameters. A non‐classical approach based on genetic algorithms (GAs) is adopted. The proposed strategy makes use of the recently developed GA‐based method of search space reduction, which has shown to be able to accurately and reliably identify structural parameters from measured input and output signals. By modifying the numerical integration scheme, input can be computed as the parameter identification task is in progress, thereby eliminating the need to measure forces. Numerical and experimental results demonstrate the power of the strategy in accurate and efficient identification of structural parameters and damage using only incomplete acceleration measurements. Copyright © 2007 John Wiley & Sons, Ltd.     

Reconciling theory with observations: elements of a diagnostic approach to model evaluation

This paper discusses the need for a well‐considered approach to reconciling environmental theory with observations that has clear and compelling diagnostic power. This need is well recognized by the scientific community in the context of the ‘Predictions in Ungaged Basins’ initiative and the National Science Foundation sponsored ‘Environmental Observatories’ initiative, among others. It is suggested that many current strategies for confronting environmental process models with observational data are inadequate in the face of the highly complex and high order models becoming central to modern environmental science, and steps are proposed towards the development of a robust and powerful ‘Theory of Evaluation’. This paper presents the concept of a diagnostic evaluation approach rooted in information theory and employing the notion of signature indices that measure theoretically relevant system process behaviours. The signature‐based approach addresses the issue of degree of system complexity resolvable by a model. Further, it can be placed in the context of Bayesian inference to facilitate uncertainty analysis, and can be readily applied to the problem of process evaluation leading to improved predictions in ungaged basins. Copyright © 2008 John Wiley & Sons, Ltd.