基于改进SOFM的矢量量化图像压缩

在介绍矢量量化和自组织特征映射神经网络的基础上，针对基于自组织特征映射神经网络的矢量量化算法，在初始码书生成、获胜神经元搜索策略以及调整获胜码字及其拓扑领域权值等方面进行改进。实验结果表明改进算法具有合理性和有效性。     

基于二阶段禁忌算法的边坡安全模型的识别

识别岩土力学经验模型的关键是如何寻找到一个全局最优解。禁忌虎法是一种寻找全局最优解的算法。针对常规禁忌算法处理连续问题时搜索范围小，对初始点的依赖性强等不足，对算法进行了改进，并将禁忌算法的离散化过程进行了修改，提出了二阶段禁忌算法。用该算法对圆弧和楔体破坏边坡数模型中的参数进行了搜索。结果表明，该方法是一种行之有效的全局优化算法。     

弃书不易

昨天,妻子说让我把那些旧书挑挑卖了,好腾出些地方。我想也是,这屋里也真有些“书满为患”了。但是,我满屋子折腾了两三个钟头,结果是一本本又码到书柜里去了。我很无奈地对妻子说：“看来,弃书不易啊”。     

基于粒子群算法的岩体结构面产状模糊C均值聚类分析

结构面产状分析是进行岩体力学分析及稳定性评价的基础,玫瑰花图、等密度图等传统的图形分析方法较为粗糙,无法对产状数据进行准确分析,采用模糊聚类方法则可以得到较为准确的优势产状,但需要事先指定分组数及初始聚心,且模糊聚类算法为局部寻优算法,初始划分对最终的数据分析结果影响较大。为了得到较为客观的分组结果及优势产状,同时能够针对大量结构面产状数据进行聚类分析,提出了基于粒子群算法的岩体结构面产状模糊C均值聚类算法。采用粒子群算法进行模糊C均值聚类算法初始聚心的求解,在计算过程中可同时确定最佳分组数,避免了人为指定的主观性,克服了模糊C均值聚类算法易陷入局部极小值和对初始划分敏感的不足。最后,通过工程实例中不同方法的聚类效果对比分析该算法的有效性,并将该方法应用于实测结构面产状数据的分析,得到较为符合实际的优势结构面分组。     

用MCS-51汇编实现BCH码的编码与译码

探讨在数据通信中用软件算法进行编码、解码和差错控制,以代替硬件功能。BCH码是通信中较为成熟的一种编码,文中详细介绍了用编程实现BCH[15,7]的编码、纠错与译码的原理,并给出了在51系列单片机上的算法流程与汇编语言源程序。在纠错译码方面采用了捕错译码法,收到了较好的效果。     

地震反演与非线性随机优化方法

地震反演问题常常需要一些非线性全局最优化的方法。近年来，基于生物学、物理学、人工智能和一些非线性科学而发展了一些具有全局优化性能且通用性强的随机搜索算法，如：遗传算法、模拟退火、禁忌搜索和混沌搜索等。作者主要针对地震勘探反演问题的应用综述了这四种非线性随机优化方法的原理和特点，并对它们的性能作了一定的分析和比较。     

基于改进遗传算法的岩体结构面产状聚类分析

根据产状对结构面进行分组是研究岩体结构的重要环节。传统分组方法通常需要依靠地质经验,缺乏客观性,而现有的聚类方法也存在一些缺陷。基于变长度字符串遗传算法,提出了一种改进的K均值算法,实现了岩体结构面产状的自动聚类。该方法的核心思想是使用遗传算法为K均值算法选择恰当的聚类中心,克服了K均值(K-means)算法受初始聚类中心影响,易收敛于局部最优解的缺陷。由于使用了变长度字符串,该方法能够在聚类过程中自动确定最佳结构面组数,同时提供最优的分组结果。针对产状数据,提出了一种新的变异方法,该方法利用C++语言实现,并被应用于浙江省某地下水封洞库结构面产状数据的分析,得到较为合理的分组结果,证明了该方法的有效性。     

地下工程围岩位移反分析的改进模拟退火算法

本文针对地下工程围岩位移反分析问题的目标函数存在多个局部极值的特点，在对模拟退火算法进程中控制参数，即初始温度、每一温度下的状态选取次数和退火策略的确定方法加以改进的基础上．引进有限元分析手段和自适应的思想，建立了基于改进模拟退火算法的位移反分析方法，并开发了相应的分析程序。工程实践分析表明：本文理论计算结果与实测结果吻合良好，该方法较一般模拟退火算法具有明显的优越性。     

基于改进粒子群算法的叠前弹性阻抗反演

弹性阻抗反演是结合声阻抗反演与AVO反演的叠前地震反演技术,能够克服叠后波阻抗反演的缺陷,反映振幅随偏移距变化的信息,已经广泛应用于地震岩性识别和流体特征的获取。常规的线性迭代弹性阻抗反演方法存在依赖初始模型、容易陷入局部极值等缺陷。针对这一问题,提出了一种基于改进粒子群算法的弹性阻抗非线性反演方法,并利用该算法对胜利油田某工区地震资料进行了弹性阻抗反演,获得了多个弹性参数剖面,与实际钻井结果相符,该方法为复杂油气藏的勘探开发提供了一种有效可行的途径。     

P—Ⅲ型分布φP值通用算法的研究

指数Γ分布（含Ｐ—Ⅲ型分布）曲线中离均系数ΦＰ值的计算方法，是水文频率分析研究的难点之一。目前，在实际工作中应用的方法都有一定的缺陷。为此，对其数学表达式进行了变换，把它归纳为求解标准化Γ分布分位数的值，并给出了其数值计算的通用算法模型，然后对Ｐ—Ⅲ型分布ΦＰ值和ＳＰ值的计算方法进行了研究。通过实践证明，其通用算法的数学模型具有算法简便、求解灵活、计算精度高、节省存储空间、通用性强、收敛速度快、数值稳定性好等优点     

The S-type Ladybird leucogranite suite of southeastern British Columbia: Geochemical and isotopic evidence for a genetic link with migmatite formation in the North American basement gneisses of the Monashee complex

The 62–52 Ma Ladybird granite (LBG) suite is a peraluminous, leucocratic, S-type, quartz monzonitic to granitic suite which occurs as batholiths, stocks, dikes, sills, and pegmatite veins predominantly in the high-grade rocks of the Shuswap complex, in southeastern British Columbia. The emplacement of the LBG was synchronous with the production of abundant migmatites within Thor–Odin dome of the Monashee complex, an exposure of North American basement, exhumed from depths of ca. 26–33 km by Eocene extensional faults. The LBG and the leucosome in migmatites from Thor–Odin dome have similar major and trace element patterns, and are both characterized by zircons which have inherited Precambrian cores. Whole rock Nd isotope compositions show a range of values for the LBG with εNd_{(55 Ma)} values from − 5.0 to − 17.2. The εNd_{(55 Ma)} for the leucosome samples range from − 9.5 to − 23.6, overlapping with those of the granitic suite. These data support the interpretation of a genetic link between formation of the LBG suite and melting of North American basement rocks, such as those exposed in the core of Thor–Odin dome. The leucosome samples have lower high field strength element (HFSE) concentrations and positive Eu anomalies, whereas the LBG samples have higher HFSE concentrations and negative Eu anomalies. The similar trace element characteristics suggest that the leucosome from the migmatites and the LBG are related, whereby most of the leucosome samples are cumulates and the LBG samples represent evolved or residual melts. The initial ⁸⁷Sr/⁸⁶Sr isotope values for both the LBG and leucosome samples have a large range. However, the initial Sr isotopic ratios for the LBG suite are lower than those of the leucosome samples, with ⁸⁷Sr/⁸⁶Sr_{(55 Ma)} ranging from 0.70603 to 0.73688 and 0.74256 to 0.76593, respectively. This isotopic discrepancy suggests either: a) isotopic disequilibrium during partial melting in the mid- to lower crust where the leucosome formed, b) the distribution of Sr during partial melting was controlled by different melt-producing reactions, and/or c) isotopic heterogeneity in the source rocks. At least part of the LBG suite likely formed via melting of North American basement rocks that were dominantly of sedimentary origin. Melting of the Proterozoic supracrustal metasedimentary rocks overlying North American basement may also have contributed to the formation of the different phases of the suite found at the regional scale. However, the abundant leucosomes in the basement rocks of Thor–Odin dome may mark the paths along which anatectic melt migrated in the structurally overlying Ladybird granites of the South Fosthall pluton.     

A hybrid method for grade estimation using genetic algorithm and neural networks

In the present paper, a new hybrid method is proposed for grade estimation. In this method, the multilayer perceptron (MLP) network is trained using the combination of the Levenberg–Marquardt (LM) method and genetic algorithm (GA). Having a few samples for grade estimation, it is difficult to get a proper result using some function approximation methods like neural networks or geostatistical methods. The neural network training methods are very sensitive to initial weight values when there are a few samples as a training dataset. The main objective of the proposed method is to resolve this problem. Here, our method finds the optimal initial weights by combining GA and LM method. Having the optimal initial values for weights, the local minima are avoided in the training phase and subsequently the neural network sustainability is trained optimally. Furthermore, the hybrid method is applied for grade estimation of Gol-e-Gohar iron ore in south Iran. The proposed method shows significant improvements compared to both conventional MLP and Kriging method. The efficiency of the proposed method gets more highlighted when the training data set is small.     

TLM法在二维非均匀介质电磁场计算中的应用

传输线模型方法(Transm ission Line Modeling,TLM)是近年来发展起来的描述快速电磁场现象的分支。我们将TLM方法应用于二维介质电磁场的计算,并且详细地阐述了该算法的实现过程。在数值实验中,分别使用TLM法、有限差分法计算各向同性介质中的静电场的分布,通过对结果进行对比分析,证明了TLM方法具有较高的精度,并且用TLM方法计算电磁场相当直观。同时,还用TLM法计算了在二维非均匀各向同性介质中,点电流源情况下研究区域中的电位分布,其结果较为理想。     

An intelligent response surface method for analyzing slope reliability based on Gaussian process regression

Problems in geotechnical engineering inevitably involve many uncertainties in the analysis. Reliability methods are important for evaluating slope stability and can take the uncertainties into consideration. In this paper, a novel intelligent response surface method is proposed in which a machine learning algorithm, namely Gaussian process regression, is used to approximate the high-dimensional and highly nonlinear response hypersurface. An iterative algorithm is also proposed for updating the response surface dynamically by adding the new training point nearest to the limit state surface to the initial training database at each step. The proposed Gaussian process response surface method is used to analyze three different case studies to assess its validity and efficiency. Direct Monte Carlo simulation is also carried out in each case to serve as the benchmark. Comparing with other methods confirms the accuracy and efficiency of the novel intelligent response surface method, which requires fewer performance function calls and avoids the need to normalize the correlative non-normal variables.     

波阻抗反演中的全局寻优策略

针对常规基于模型的波阻抗反演方法严重依赖于初始模型的选择和易陷入局部最优等局限性，提出了一种新的全局寻优策略。该反演策略是在常规测井约束反演的框架中加入一定次数的遗传全局搜索机制。如果迭代过程一旦陷入局部最优解；就可以把已经形成的局部最优解作为寻优的新起点，在此基础上进行全局遗传寻优，搜索更优的反演结果。通过模型数值计算和实际资料处理，表明该反演策略具有跳出初始模型控制的优良性能和良好的实际反演效果。     

人工冻土施工方法的现状及趋势

本对冻土的施工方法即钻爆法和机械挖掘法进行了回顾，实践证明，采用钻爆法施工比使用风镐掘进速度提高４倍左右，机械挖掘法国内尚处于试验改进阶段，对目前施工中存在的问题进行了讨论。     

Evaluate the performance of an accelerated initial stiffness method in three dimensional finite element analysis

Newton’s method is a commonly used algorithm for elasto-plastic finite element analysis and has three common variations: the full Newton–Raphson method, the modified Newton–Raphson method and the initial stiffness method. The Newton–Raphson methods can converge to the solution in a small number of iterations when the system is stable; however, the methods can be quite computationally expensive in some types of problems, for example where the tangent stiffness matrix is unsymmetric or the plasticity is highly localized. The initial stiffness method is robust in those cases but requires a larger number of iterations. This prompted the formulation of many acceleration techniques in literature. In this paper, those techniques will be briefly discussed. This will be followed by the development of a modified acceleration technique for the initial stiffness method. The performance of the modified accelerated initial stiffness method will be examined in elasto-plastic analyses, using both direct and iterative matrix solvers. The results will be compared – in terms of the required number of iterations and the computation time – with an existing accelerated initial stiffness method, the non-accelerated initial stiffness method and the Newton–Raphson tangent stiffness method.     

地下水模型的快速自适应组合网格求解方法

本文针对当前地下水模型中包括断裂、防渗帷幕在内的线形水文地质对象(L ineStyle Hydrogeological Ob ject)的模拟难点,研究基于重叠型区域分解原理的快速自适应组合网格方法(Fast Adaptive Composite G rid—FAC)。论文首先概括当前线形水文地质对象的模拟手段及其存在的不足,进而讨论FAC方法建立和求解地下水模型的基本原理。通过对理想的地下水流模型的求解,表明该方法能够满足线形水文地质对象的精细模拟求解的要求,且求解效率较高。     

南海北部似海底反射层速度结构全波形反演

似海底反射层的速度异常是识别天然气水合物的重要标志,这里提出了一种针对天然气水合物似海底反射层的全波形反演方法。这种方法分为全局搜索与局部搜索二部份:首先使用遗传算法进行旅行时,反演得到背景速度模型;然后用其作为初始模型,使用共轭梯度算法进行全波形反演。通过对含噪数据的数值试验,算法表现出了较高的稳定性,并确定了进行全波形反演的遗传算子。将这种波形反演方法应用于我国南海北部海域的天然气水合物研究,反演得到了分辨率高于常规速度分析的似海底反射层速度结构,并识别出似海底反射层的速度异常。利用纵波速度反演的结果,计算出沉积物中游离气的含量,认为BSR下方的低速层可以解释为含至少1%游离气的薄层。并分析了研究区内甲烷气的来源,认为该区域游离气兼有生物气和热解气。