福建东山岛矿产资源开发利用与生态环境保护初论

就东山岛在水、砂、石、土的开发利用中存在的问题,阐述了开发利用矿产与保护生态环境之间的辩证关系,提出东山县应做好矿产资源开发利用与“建设港口旅游城市”的规划,走资源节约型的发展海洋经济建设的新路子,促进东山县经济的可持续发展。     

水-岩作用的线性规划模型与应用研究——以溪洛渡水电工程为例

采用水-岩作用热力学模拟的方法,以溪洛渡水电站工程为实例,从水化学方面对坝区复杂水文地质条件作了定量分析评价。研究成果充分反映了水-岩作用这种物理化学反应的结果,同时也为正确评价溪洛渡水电站复杂水文地质条件提供了可靠的依据。     

南沙群岛海域浅海水深提取及影像海图制作技术

研究了南沙群岛海域TM图像提取浅海水深的模型和方法以及影像海图制作技术。在传统的多波段线性回归模型的基础上,引入数据分组平均预处理、潮汐改正、分段线性回归和数据归一化等技术,使改进后的模型更加合理并具有较高的精度,从而适用于大的海域。在此基础上,提出了一整套遥感影像海图制作的技术和工艺流程。     

成矿系统的结构与聚矿功能

成矿系统结构对成矿动力学条件的约束与促进,引起系统固有聚矿功能的巨大变异。成矿系统动力学包括：系统运转的动力组合、系统物质运动总方向和轨迹、矿质活动空间规模形态及单位空间中成矿微过程的频度。系统结构定性分析表明：系统结构的完善程度和成矿动力学条件的优劣与系统聚矿功能的强度正相关。系统结构完善程度可由结构紧致度（Ｉ）表征,系统聚矿功能可用标准富集量（Ｑｓ）反映,它是矿床储量（Ｑ０）经成矿难度系数（Ｃ）变换的归一化指标。经结构定性半定量分析,对成矿系统聚矿功能作出初步排序,具强烈非线性成矿特征的花岗岩浆成矿系统和环流热液成矿系统的聚矿功能最高     

非精确搜索一维全局最优化方法

研究一维全局最优化问题的确定性求解方法。运用逐次建立目标函数的线性下界函数,将不含全局最优解的子区域删除,并基于非精确搜索结合下降算法而得出非精确搜索一维全局最优化方法,使计算量减少且使迭代收敛加快。迭代结束时该算法得到一维全局最优化问题的ε－全局最优解。该方法具有有限收敛性且不需精确的局部优化过程。文中的数值实例表明该算法的有效性。     

数值代数的几项进展及待解决的问题

近５０年来,数值线代数取得了大量的研究成果。文中就关注并感兴趣的几项进展给予简要介绍。同时也概述若干值得深入研究的问题。第一部分以几部专著为线索回顾８０年代以前的主要进展;第二部分介绍８０年代以来的几项进展;第三部分指出一些有待深入研究的问题。     

常Q滞弹性介质地震波动数值模拟——时域本构优化逼近

在地震波动模拟中计入常Q滞弹性阻尼,可有效降低模拟波形的误差.就时域有限差分和有限元模拟而言,常基于广义标准线性体建立阻尼介质的时域本构逼近.广义标准线性体由若干标准线性体并联得到,增加标准线性体个数能有效提高模拟精度,但计算量及计算存储将成倍增长.目前尚未有普适的标准线性体个数优化取值方案.本文基于广义标准线性体参数的非线性优化拟合方法,详细分析了时域本构逼近误差的影响因素,清楚揭示了逼近误差仅取决于频带宽度,与频带上下限取值无关这一特性,阐明了构建具有普适性标准线性体个数优化取值方案的可行性.论证了波形模拟精度主要取决于波传播距离与模拟波长的比值以及标准线性体的个数取值.综合考虑上述两个控制因素,结合在波动正反演问题中广为采纳的波形时频误差衡量准则,对不同Q值介质给出了标准线性体个数优化取值表.进一步,本文提出采用不同个数标准线性体以近似不同Q值的阻尼介质时域本构,解决了以往波动数值模拟中统一采用相同个数标准线性体而导致的计算量及计算存储浪费或模拟精度低下等问题,并基于数值实验验证了这一方法的精度.本文工作对推进滞弹性介质波动数值模拟及其在全波形反演问题中的应用具有理论价值和实践意义.     

A model‐based data‐driven dictionary learning for seismic data representation

Planar waves events recorded in a seismic array can be represented as lines in the Fourier domain. However, in the real world, seismic events usually have curvature or amplitude variability, which means that their Fourier transforms are no longer strictly linear but rather occupy conic regions of the Fourier domain that are narrow at low frequencies but broaden at high frequencies where the effect of curvature becomes more pronounced. One can consider these regions as localised “signal cones”. In this work, we consider a space–time variable signal cone to model the seismic data. The variability of the signal cone is obtained through scaling, slanting, and translation of the kernel for cone‐limited (C‐limited) functions (functions whose Fourier transform lives within a cone) or C‐Gaussian function (a multivariate function whose Fourier transform decays exponentially with respect to slowness and frequency), which constitutes our dictionary. We find a discrete number of scaling, slanting, and translation parameters from a continuum by optimally matching the data. This is a non‐linear optimisation problem, which we address by a fixed‐point method that utilises a variable projection method with ?₁ constraints on the linear parameters and bound constraints on the non‐linear parameters. We observe that slow decay and oscillatory behaviour of the kernel for C‐limited functions constitute bottlenecks for the optimisation problem, which we partially overcome by the C‐Gaussian function. We demonstrate our method through an interpolation example. We present the interpolation result using the estimated parameters obtained from the proposed method and compare it with those obtained using sparsity‐promoting curvelet decomposition, matching pursuit Fourier interpolation, and sparsity‐promoting plane‐wave decomposition methods.     

Water temperature modelling: comparison between the generalized additive model,logistic, residuals regression and linear regression models

Water temperature has a significant influence on aquatic organisms, including stenotherm fish such as salmonids. It is thus of prime importance to build reliable tools to forecast water temperature. This study evaluated a statistical scheme to model average water temperature based on daily average air temperature and average discharge at the Sainte-Marguerite River, Northern Canada. The aim was to test a non-parametric water temperature generalized additive model (GAM) and to compare its performance to three previously developed approaches: the logistic, residuals regression and linear regression models. Due to its flexibility, the GAM was able to capture some of the nonlinear response between water temperature and the two explanatory variables (air temperature and flow). The shape of these effects was determined by the trends shown in the collected data. The four models were evaluated annually using a cross-validation technique. Three comparison criteria were calculated: the root mean square error (RMSE), the bias error and the Nash-Sutcliffe coefficient of efficiency (NSC). The goodness of fit of the four models was also compared graphically. The GAM was the best among the four models (RMSE = 1.44°C, bias = ?0.04 and NSC = 0.94).     

Temporal and spatial variations of potential evaporation and the driving mechanism over Tibet during 1961–2001

Potential evaporation (PE) is the basic component of the global hydrological cycle and energy balance. This study detected the temporal and spatial variations of PE and related driving factors in Tibet, China, for the period 1961–2001, based on observed data recorded at 22 meteorological stations. The results showed that (1) Tibet experienced a statistically significant decrease of PE between 1961 and 2001, which started mainly in the 1980s, along with accelerated warming; (2) the mean annual PE in Tibet showed an east–west increasing trend, and the annual PE at most stations presented decreasing trends; (3) an inverse correlation of mean annual PE with elevation was detected (low–high decreasing trend), and the statistical equations to estimate PE were established based on longitude, latitude and elevation; and (4) PE in Tibet can be well expressed by related meteorological variables, with vapour pressure deficit the dominant factor in determining PE.

EDITOR Z. W. Kundzewicz ASSOCIATE EDITOR not assigned