小波框架的彩色图像泊松去噪

噪声是影响图像质量的重要因素,噪声的存在导致图像的某些特征细节不能被辨识以及图像的信噪比下降,所以图像去噪是图像处理中的一个重要问题.本文提出了基于小波框架的彩色图像的泊松去噪模型.在该模型中,赋权的l²项作为保真项,包含小波框架的l¹项作为正则项.同时,又提出了解决该模型的重新赋权的split Bregman算法.最后,利用仿真实验以及PSNR（峰值信噪比）指标对该模型的去噪效果进行评估,评估结果表明该算法可行、有效.     

组合数学在计算机科学中的应用

介绍了组合数学的概念、起源与研究的主要内容,分析了组合数学的特点,阐述了组合数学与计算机软件的联系,并着重通过两个例子说明了Ramsey数在计算机科学的信息检索、分组交换网设计分支中的重要应用.     

A digital elevation analysis: a spatially distributed flow apportioning algorithm

An integrated flow determination algorithm is proposed to calculate the spatial distribution of the topographic index to the channel network. The advantages of a single flow direction algorithm and other multiple flow direction schemes are selectively considered in order to address the drawbacks of existing algorithms. A spatially varying flow apportioning factor is introduced to distribute the contributing area from upslope cells to downslope cells. The channel initiation threshold concept is expanded and integrated into a spatially distributed flow apportioning algorithm to delineate a realistic channel network. The functional relationships between the flow apportioning factors and the expanded channel initiation threshold (ECIT) are developed to address the spatially varied flow distribution patterns considering the permanent channel locations. A genetic algorithm (GA) is integrated into the spatially distributed flow apportioning algorithm (SDFAA) with the objective function of river cell evaluation. An application of a field example suggests that the spatially distributed flow apportioning scheme provides several advantages over the existing approaches; the advantages include the relaxation of overdissipation problems near channel cells, the connectivity feature of river cells and the robustness of the parameter determination procedure over existing algorithms. Copyright © 2004 John Wiley & Sons, Ltd.     

位错模式反演的算法研究

综述了大地测量反演算法的发展状况，详细介绍了模拟退火，随机耗费和区间算法等3种优化方法，并基于位错模式，采用模拟的重力测量观测数据，比较了3种算法的反演效果，结果表明：模拟退火法优于随机耗费法，而区间算法的可靠性又优于模拟退火法，区间算法是最可靠的反演方法。     

Evaluation and forecasting of daily groundwater outflow in a small chalky watershed

The purpose of this research is to include expert knowledge as one part of the modelling system and therefore offer the chance to create a productive interaction system between expert, mathematical model (MMO8) and artificial neural networks (ANNs). In the present project, the first objective is to determine some parameters by the MMO8 model, introduced as ANN input parameters to forecast spring outflow. The second objective is first to investigate the effect of temporal information by taking current and past data sets and then to forecast spring outflow. The good results obtained reveal the merit of the ANNs–MMO8 combination, and specifically multilayer perceptron (MLP) models. This methodology, for a network with lower, lag and number hidden layer, consistently produced better performance. Copyright © 2003 John Wiley & Sons, Ltd.     

四川旱涝震灾害的人工神经网络外推预测

选取旱、涝、震灾害之间的一步转移概率作为Ｂ－Ｐ人工神经网络训练样本的输入信息，建立了四川旱、涝、震的人工神经网络灾型预测模型。Ｂ－Ｐ网络模型应用于实例预测结果与用主分量分析法的趋势预测结果精度接近。     

基于树的多关键词搜索算法在网络监控系统中的应用

介绍了基于树的多关键词快速文本搜索算法，并针对该算法在实际应用中的问题提出了改进措施，在不增加预处理时间和内存空间消耗的前提下有效避免搜索中漏搜和多搜，无损于该算法的高效性。     

Statistical significance of modal parameters of bridge systems identified from strong motion data

Modal parameters of structural systems have commonly been determined using system identification (SI) methods for damage detection and health monitoring. For determining the deterioration of the integrity of structural systems correctly, modal parameters of a healthy structure have to be obtained with adequate certainty so that these parameters can be used as reliable references for the healthy system to compare with those of the damaged system. In this study, the statistical significance of modal parameters identified using strong motion time histories recorded on two bridge structures is assessed. The confidence intervals of identified modal frequencies and damping ratios are obtained using Monte Carlo simulations and sensitivity analyses in conjunction with eigenrealization algorithm. The dependence of the statistical bounds on model parameters is examined. The effect of using different number of sensors on the statistical significance is evaluated using simulated time history data from a validated finite element model of a bridge. Copyright © 2005 John Wiley & Sons, Ltd.     

论多种数据联合反演的模式及算法

针对日益丰富的数据资料，综述了大地测量反演的发展进程，论述了多种数据联合反演的意义和必要性，给出了兼顾权比确定的大地测量、地震和地质三类数据的联合反演模式及采用水准测量、GPS和重力三种数据联合反演断层参数的具体公式，特别介绍了求解优化问题所有全局最优解的区间算法，并给出了基本算例，结果体现了区间算法无可比拟的优越性及其在大地测量反演领域中的应用前景。     

山东半岛近岸海带养殖活动对水体光学吸收特性的影响

为了研究近岸海带养殖活动对水体光学特性的影响,本文选取山东半岛黑泥湾海域为典型研究区,利用2021年4月和8月在该区的9站同步观测数据,分析其总悬浮颗粒物、藻类颗粒物、非藻类颗粒物以及有色溶解有机物的吸收特性,并计算各组分对总吸收系数的贡献率,同时采用Quasi-analytical algorithm (QAA)算法借助MODIS影像反演了水体总吸收系数,结合实测数据获得了黑泥湾水体吸收特性的季节变化情况。结果表明,有海带养殖季节表层水体藻类颗粒物、非藻类颗粒物、总颗粒物和有色溶解有机物的吸收系数明显大于无海带养殖季节,且春季海带养殖区水体的总吸收系数大于无海带养殖区;海底表层沉积物的再悬浮造成底层吸收系数较大,而在春季成熟期的海带汇聚较大量的有机物质导致中层藻类颗粒物吸收系数相对较高;参考波长向红波移动,QAA_v5算法能够较好地估算该区表层水体吸收系数,且在海带养殖季节水体组分会影响到更长的波段特征。本研究可为深入了解海带养殖对水体各组分浓度和分布、碳循环以及水生生态系统的结构和功能的影响提供参照,并有助于提高近岸水体组分的遥感反演精度。