基于空间聚类的城镇土地定级方法研究

分析了多因素综合评定法、级差收益测算法等城镇土地定级方法的不足，提出了基于空间聚类的地价分区定级法的主要思想和主要步骤，并以石狮市土地定级为例，验证了此方法。     

一种基于区域生长原理的油库目标聚类定位方法

利用油罐目标相对集中而虚假目标相对较离散的分布特点,提出了一种基于区域生长原理的聚类方法.对于实际的遥感光学图像,所提方法既能将油罐目标聚类定位油库区域,又能自动去除虚假油罐目标.实验表明,该方法在油库检测定位上准确率高,是一种实用有效、运算量小的聚类方法.     

基于路径的聚类分析

聚类分析的很多算法中都采用连接两点直线的欧氏距离来判断空间亲疏性,然而当有障碍物层存在时,连接两点的直线已不能完全表达它们之间的关系,特别是当有指定的交通路线时,两点之间的连通路径和距离必须遵从特定的路径。文中讨论在了障碍物或指定的交通路线存在的情况下点集的聚类分析,给出了解决有障碍物或指定交通路线时进行聚类分析的算法PathClust。     

关键海区海温异常的变化与中国区域降水和气温的关系

利用 １９５１年到 １９９８年的月平均海温资料及同时期中国 １６０个测站的降水和气温的月平均资料,选用海温异常的变化趋势一变温,讨论了关键海区海温异常的变化与我国降水和气温的关系,旨在探讨变温因子与我国降水和气温的关系与海温距平与降水和气温的关系有什么不同,用变温因子能否降低降水预报的不确定性。结果表明：降水异常对海温异常两种变化趋势的响应不完全相同,说明分别讨论同一种海温异常态的两种变化趋势对降水的影响比单独讨论海温距平对降水的影响更有效一些,有助于降低预报的不确定性;除西太平洋海区外,气温异常对各海区海温异常两种变化趋势的响应较一致。降水异常对变温的响应与对海温异常的响应,有一致之处,也有不同之处。     

Elastic-anelastic Regional Structures for the Iberian Peninsula Obtained from a Rayleigh Wave Tomography and a Causal Uncoupled Inversion

The elastic and anelastic structure of the lithosphere and asthenosphere of the Iberian Peninsula is derived by means of tomographic techniques applied to local phase and group velocities and local attenuation coefficients of Rayleigh wave fundamental mode. The database consists of surface wavetrains recorded at the broadband stations located in the Iberian Peninsula on the occasion of the ILIHA project. Path-averaged phase and group velocities and attenuation coefficients were previously obtained by standard filtering techniques of surface wavetrains and, subsequently, local dispersion curves were computed according to the Yanovskaya-Ditmar formulation. First, a principal component analysis (PCA) and the average linkage (AL) clustering algorithm are applied to these local values in order to classify the Iberian Peninsula in several rather homogeneous domains from the viewpoint of the similarity of the corresponding local dispersion curves, without previous seismotectonic constraints. Second, averaged phase and group velocities and attenuation coefficients representing each homogeneous region are used to derive the respective elastic and anelastic models of the lithosphere and asthenosphere. This purpose is achieved by using the uncoupled causal inversion of phase and group velocities and attenuation coefficients. The main features of the homogeneous regions are discussed by taking as reference the Hercynic, Alpine and Neogene domains of the Iberian Peninsula, and two questions affecting the reliability of the elastic-anelastic models are revised. First, the coherence of the shear-velocity and Q_β⁻¹ models obtained by causal uncoupled inversion for each region is analysed. Second, the influence of the causal phase and group velocities on the shear-velocity models is evaluated by comparing elastic and anelastic models derived from causal uncoupled inversion with those deduced from non-causal inversion.     

地震临界丛集的判定及其应用

介绍了地震临界时间丛集的判定方法——时间结构变异诊断方法。把时间结构变异诊断方法运用于1999年岫岩地震序列及中国大陆强震活动特性研究，并按此方法预测了中国大陆未来大震可能发生的时间点。研究认为，时间结构变异诊断法不仅可以用作前震序列和余震序列以及正常震群活动的判断，同时也适用于区域地震活动状态的描述。震例研究表明，时间结构变异诊断法在地震预测中具有实际意义。     

计算机多元统计在渔船主要参数分析中的应用

本文用多元统计方法在计算机上对我国目前广泛使用的36种漁船作了对应分析和动态聚类分析。其中9个指标为CB、Cp、Cw、L/B、L/D、B/D、B/T、VF/LBD和P/△。漁船被聚成三类。其中参数P/△、VF/LBD对聚类起最大作用。     

层状云中对流泡特征及其在降水场中的作用

层状云中夹有对流泡对整个雨系降水的启动、发展以及降水场的分布、变化有很大作用，对寻找人工增雨最佳人工影响潜力区也有特殊意义。该文在总结大量历史资料的基础上，利用雷达、卫星、地面实况、天气、机载云雨探测和数值模拟等各种手段，对层状云中夹着的对流泡进行系统深入地研究，进而为人工增雨作业提供依据。     

近、现代黄河三角洲统计分布特征浅析

1855年以来建造的近、现代黄河三角洲是我国三大河口三角洲之一,由7个亚三角洲堆积体组成。在缺少实验室数据的情况下,尝试利用陆地卫星TM遥感数据,进行比值和主成份分析,增强含铁氧化物光谱信息同时分析了7个亚三角洲堆积体的频率分布直方图和统计特征值(均值、标准离差)。在此基础上,简要论述了近、现代黄河三角洲地表环境的差异,为利用遥感技术解决地学问题提供了一条有益的思路.     

The Statistical Prediction Of Offshore Winds From Land-Based Data For Wind-Energy Applications

Land-based meteorological measurements at two locations on the Danish coast are used to predict offshore wind speeds. Offshore wind-speed data are used only for developing the statistical prediction algorithms and forverification. As a first step, the two datasets were separated into ninepercentile-based bins, with a minimum of 30 data records in each bin. Next, the records were randomly selected with approximately 70% of the data in each bin being used as a training set for development of the prediction algorithms, and the remaining 30% being reserved as a test set for evaluation purposes. The binning procedure ensured that both training and test sets fairly represented the overall data distribution.To base the conclusions on firmer ground, five permutations of these training and test sets were created. Thus, all calculations were based on five cases, each one representing a different random selection from the same data, but maintaining the (approximate) 70-30 split in each bin. This procedure served to ensure that conclusions were not based on a single randomly-selected case. Two statistical methods are employed:multiple linear regression (MLR), and Classification and Regression Trees(CART). MLR produces excellent results using only land-based predictors.The CART results are similar to those from MLR, and tend to be slightly better.Retired