基于SAVEE方法的海岛空间价值评价——以南沙群岛为例

对SAVEE评价方法的理论基础、分析步骤、应用条件和优缺点进行了系统归纳和总结,构建了SAVEE评价分析模型。以南沙群岛的空间价值评价为例开展实证研究,尝试将SAVEE方法应用于海岛空间价值评价。结果表明:SAVEE评价法计算简便,可操作性强,能够量化体现每个因子价值,评价结果清晰易懂。SAVEE为空间价值评价方法提供了新的选择,具有极大的应用前景。     

基于自适应网络模糊推理方法在河道洪水预报中的应用

对于易受洪灾的地区而言,快速而准确的洪水预报非常重要,能够为洪水预警消息的发布提供更长的先导时间,从而为可能受灾地区的人们提供更充足的时间以采取相应的防洪措施或安全转移。 常用的预报模型包括基于物理性模型和基于系统技术模型。尽管物理性模型能对洪水形成的物理过程提供很好的解释, 水文学家并不愿意使用它们,因为模型中参数的率定是比较复杂的。因此,一种基于纯数据集的黑箱技术已被广泛采纳。常用的黑箱模型包括线性模型(LR)、自回归移动平均模型(ARMA)和人工神经网络模型（ANN）等。 在当前的研究中,一个相对新颖的黑箱模型--基于自适应网络的模糊推理系统（ANFIS）被用来对长江某河段的洪水进行预报。与此同时,一个线性回归模型（LR）用来作为ANFIS模型的对照。在构建ANFIS中,混合学习算法 (即误差反衍（BP）耦合最小二乘法（LSE）) 用来训练模型的参数。此外,为避免出现过度训练现象,原始数据集基于统计特征值划分成3个子集：训练集、测试集和校正集。当对ANFIS模型训练时,测试集用来帮助控制训练代数。结果表明,ANFIS的预报效果优于LR模型。分析认为ANFIS能够提供预报精度是因为其采用了局部拟合技术,通常它会优于LR模型所采用的全局拟合技术。最后,对本研究而言,最适合的ANFIS模型是输入量为梯形的成员度函数。     

Maximum likelihood fitting of the Poisson lognormal distribution

In this paper some properties and analytic expressions regarding the Poisson lognormal distribution such as moments, maximum likelihood function and related derivatives are discussed. The author provides a sharp approximation of the integrals related to the Poisson lognormal probabilities and analyzes the choice of the initial values in the fitting procedure. Based on these he describes a new procedure for carrying out the maximum likelihood fitting of the truncated Poisson lognormal distribution. The method and results are illustrated on real data. The computer program for calculations is freely available.

夜光藻赤潮与环境因子关系的模糊分析

针对在2006年夏天渤海湾赤潮重点监控区中发生的一次夜光藻赤潮,考虑到夜光藻赤潮过程与环境因子的复杂关系和赤潮监测数据的不确定性,利用模糊逻辑方法对监测数据样本进行了分析。本文的研究对象为1号、2号和4号站位包含有夜光藻赤潮过程的7月26日~8月20日的连续监测数据,给出了隶属度函数和模糊规则的提取方法,利用生成的模糊逻辑规则阐述了此次夜光藻赤潮的生消过程并分析了夜光藻赤潮与若干环境因素之间的变动关系,为进一步研究该海域的夜光藻赤潮机理并预测夜光藻赤潮奠定了基础。     

Hierarchical spatial point process analysis for a plant community with high biodiversity

A complex multivariate spatial point pattern of a plant community with high biodiversity is modelled using a hierarchical multivariate point process model. In the model, interactions between plants with different post-fire regeneration strategies are of key interest. We consider initially a maximum likelihood approach to inference where problems arise due to unknown interaction radii for the plants. We next demonstrate that a Bayesian approach provides a flexible framework for incorporating prior information concerning the interaction radii. From an ecological perspective, we are able both to confirm existing knowledge on species’ interactions and to generate new biological questions and hypotheses on species’ interactions.

Multiple batch extraction test to estimate contaminant release parameters using a Bayesian approach

Industrial activities produce vast amounts of weakly contaminated materials which are commonly reused as filling materials on natural ground. There is a strong demand to define guidelines for the application of these materials, to estimate the leaching potential of contaminants from the materials, and to assess the potential hazard for groundwater pollution. We present a multiple batch experiment, where measurements of liquid-phase concentrations at varying liquid/solid ratios are used to estimate the total mass of contaminant that can be extracted from a contaminated material with a mild extractant like water. Furthermore, the experiment yields estimates of the isotherm describing the partitioning of the contaminant between the solid and liquid phases, and a concentration that might be expected under soil hydraulic conditions representative for the field situation. Model parameters are estimated from liquid-phase concentrations within a Bayesian framework by applying the Shuffled Complex Evolution Metropolis Algorithm (SCEM-UA), an efficient Markov Chain Monte Carlo sampler. A sensitivity analysis and inversions of synthetically generated data corrupted with noise show the general suitability of the proposed method. An uncertainty analysis for model parameters and model predictions shows the expected accuracy of the estimates. An application to concentration measurements obtained from a multiple batch extraction test illustrates the applicability of the approach for a real situation.     

Univariate Bayesian nonparametric binary regression with application in environmental management

In environmental management, we often have to deal with binary response variables whose outcome dictates the course of action. This paper introduces a nonparametric Bayesian binary regression model with a single predictor variable that is more flexible than the commonly used logistic or probit models. Due to the Bayesian feature, the model can be easily used to combine observed data with our knowledge of the subject to produce site-specific results. By using three examples, this paper shows the potential application of the model in the environmental management, and its advantages in terms of flexibility in model specification, robustness to outliers, and realistic interpretation of data.     

较难注水煤层的注水工艺及参数

根据在晋城矿务局开采3~#煤层进行的注水试验,系统地介绍了较难注水煤层的注水工艺及注水参数。     

新钢烧结机尾电除尘器的扩容改造

介绍了烧结机尾电除尘改造技术参数的确定方法,改造后各项参数得到提高。     

压力容器声发射信号参数分析方法的探讨

参数分析是声发射技术应用中的重要环节之一,因为它直接关系到能否正确反映被检对象的物理状况。本文集多年检测的经验,提出了参数分析的几种方法以及参数分析中须注意的问题,力求通过参数分析方法来客观、合理地表征检测对象的物理状况。