BPM授时台至南极长城站短波场强测试分析

本文讨论了在南极长城站收测BPM授时台时号场强的实验数据并和国际广播行政大会推荐的计算方法得到的预测值进行了比较。结果表明,在此条电路上两者较吻合,均方根偏差为6.9dBμv/m,从而在实验上初步验证了FTZ方法的可用性。     

松花江哈尔滨段悬浮物含量遥感反演与克里格插值预测精度对比

以松花江干流哈尔滨段水体中悬浮物为研究对象,2012年7月14~15日,设置了11个采样断面,共33个采样点,测量得到总悬浮物含量和江面高光谱反射率数据;选用时间上较为接近的TM影像,分别用遥感反演模型(PSO-LSSVM模型)和克里格空间插值方法,对总悬浮物含量进行预测,并对使用两种方法的结果进行比较。结果表明,使用两种方法的结果的预测精度较为接近,遥感反演模型预测值的平均绝对百分误差为11.21%,均方根误差为10.05 mg/L;克里格空间插值预测结果的平均绝对百分误差为11.32%,均方根误差为10.93 mg/L;遥感反演模型预测值能较好的反映出松花江干流哈尔滨段总悬浮物含量的总体分布特征和变异特征;克里格空间插值对空间自相关小范围内具有较好的预测能力,超出自相关范围不能预测。     

附录——本会图书室收到赠书目录

脍 者︵书 名︶八册数︶气象研究所 气象月刊 第一态—第天卷︵各一卷︶四八 第六卷八第一期至第玉剁︶五 地震学报 VOll.︵NO.1—N。4︶四 V。一.2.︵NO.1—NO.2︶二 气象研究所集刊︵第一号—第三号︶ 中国气候区域论 一 极面学说与中国长江流域下游之风暴 一 亚东温带低气压之分类及冀性觉 一 气象年报︵第一怒—第三卷︶三 气象季刊︵第一忍全卷︶四 共计 六九地质研窕所 地质研究所集刊︵第一号—第十号︶一O地质研究所西文集刊︵第九号—第十三号︶五 南京龙潭地贸指南︵外附龙潭地贸图一幅︶一 地质研究所业刊︵第一号—第四号…     

附录——本会图书室收到赠书目录

脍 者︵书 名︶八册数︶气象研究所 气象月刊 第一态—第天卷︵各一卷︶四八 第六卷八第一期至第玉剁︶五 地震学报 VOll.︵NO.1—N。4︶四 V。一.2.︵NO.1—NO.2︶二 气象研究所集刊︵第一号—第三号︶ 中国气候区域论 一 极面学说与中国长江流域下游之风暴 一 亚东温带低气压之分类及冀性觉 一 气象年报︵第一怒—第三卷︶三 气象季刊︵第一忍全卷︶四 共计 六九地质研窕所 地质研究所集刊︵第一号—第十号︶一O地质研究所西文集刊︵第九号—第十三号︶五 南京龙潭地贸指南︵外附龙潭地贸图一幅︶一 地质研究所业刊︵第一号—第四号…     

城市需水量模拟及不确定性分析方法研究

需水量预测是区域水资源合理配置和有效管理的基础。由于供需水量的不确定性,精准的需水量预测较有困难。通过建立径向基函数（RBF）与BP神经网络预测模型,以西北地区城市西安市需水量为例,将用水量驱动因子作为模型输入,利用1990-2009年20组年用水数据进行网络训练模拟,对2010-2012年3组年用水数据进行检验预测,采用不确定性评价指数和置信区间方法对两种模型及模拟结果进行比较分析。结果表明,RBF与BP模型预测期的均方根误差分别为0.08、0.26,不确定性评价指数分别为0.74、1.02且BP模型预测值的相对误差最大超过10%以上,而RBF模型预测值的相对误差均小于5%,说明RBF模型模拟效果好,具有预测精度高以及不确定性影响低的双重优势;在模拟结果基础上,引用置信区间分析了结果的可靠性,为分析城市需水预测的不确定性提供了依据。     

基于统计降尺度方法的陕西省月气温预测分析

从短期气候预测的实际出发,针对月尺度的气温分县预测,使用逐步回归和主成分分析（即经验正交函数）的统计降尺度方法,利用地面观测站的气温资料、美国国家环境预报中心和美国大气科学研究中心的大尺度气候变量（NCEP/NCAR）和国家气候中心月动力延伸预报模式资料（DERF）,对1982-2015年陕西省96个县区的1月和7月气温进行预测,建立统计降尺度模型,并采用交叉检验方法检验模型的预测效果,表明基于经验正交函数和逐步回归的统计降尺度方法在陕西省1月和7月气温的预测中是合理可用的。全省96个县区1月份预测值与观测值距平符号一致率大于60%达到了50个县区,7月份大于60%达到了60个县区。预测值可以较好的预测出气温变化趋势,但预测值变化幅度明显小于观测值。     

大气中二氧化硫的灰色预测

根据灰色系统理论，联系乌鲁木齐市大气环境的实际状况，建立了精度检验为一级的灰色预测模型，经模型检验其精度完全满足要求。并对乌鲁木齐大气中的SO2值进行了预测分析，结果表明，乌鲁木齐市大气中SO2值呈上升的趋势，在未来几年中，乌鲁木齐市大气中SO2的预测值超过国家三级标准值，即SO2年均值≤0．10mg／m^3，这种发展趋势应引起有关部门的关注。     

克里雅河流域土壤盐分光谱定量分析

本文对克里雅河流域进行野外调查、采集土壤样品及其光谱反射特性的测量,通过比较不同光谱预处理的方法建立偏最小二乘回归(PLSR)模型,并利用决定系数(R2)、均方根误差(RMSEP)、残留预测偏差(RPD)对模型的稳定性和预测能力进行检验。结果表明:反射率一阶微分是预测土壤样本盐分含量的最佳光谱指标。PLSR模型在建立土壤光谱与盐分含量关系时较为适用,R2、RMSE和RPD分别为0.77、0.25和1.88。利用反射光谱估算土壤中盐分含量,通过各种光谱预处理方法可以提高估算精度,可以为该区土壤盐渍化评价和生态环境调查提供依据。     

利用神经网络对居民消费价格指数预测的研究——以广州为例

居民消费价格指数是经济地理研究的重要依据，但其运算是一个非常复杂的过程。采用归一化数据处理方法，选择神经网络的训练样本，建立基于BP神经网络的居民消费价格指数预测的数学模型。利用该模型对广州居民消费价格指数进行预测，结果表明模型的预测值与实测值的误差仅为0．91％。用神经网络来构建模型后进行预测，是一种新方法的尝试，通过检验也是可行的。用MATTLAB语言编写程序，对数据进行处理后，能预测到未来的发展情况，对相关方面起到指导作用。     

2003年10月底太阳风暴期间中山站电离层吸收效应的观测与分析

本文介绍了成像式宇宙噪声接收机技术和数据分析方法,通过对南极中山站成像式宇宙噪声接收机在2003年10月底太阳风暴期间的观测数据进行分析,得到了相应的极区电离层的吸收效应,它们主要是强度为2. 7dB的宇宙噪声突然吸收和强度高达31dB持续4d的极盖吸收。     

The use of predictive analysis in spatiotemporal crime forecasting: Building and testing a model in an urban context

Police databases hold a large amount of crime data that could be used to inform us about current and future crime trends and patterns. Predictive analysis aims to optimize the use of these data to anticipate criminal events. It utilizes specific statistical methods to predict the likelihood of new crime events at small spatiotemporal units of analysis. The aim of this study is to investigate the potential of applying predictive analysis in an urban context. To this end, the available crime data for three types of crime (home burglary, street robbery, and battery) are spatially aggregated to grids of 200 by 200 m and retrospectively analyzed. An ensemble model is applied, synthesizing the results of a logistic regression and neural network model, resulting in bi-weekly predictions for 2014, based on crime data from the previous three years. Temporally disaggregated (day versus night predictions) monthly predictions are also made. The quality of the predictions is evaluated based on the following criteria: direct hit rate (proportion of incidents correctly predicted), precision (proportion of correct predictions versus the total number of predictions), and prediction index (ratio of direct hit rate versus proportion of total area predicted as high risk). Results indicate that it is possible to attain functional predictions by applying predictive analysis to grid-level crime data. The monthly predictions with a distinction between day and night produce better results overall than the bi-weekly predictions, indicating that the temporal resolution can have an important impact on the prediction performance.     

On the prediction error variance of three common spatial interpolation schemes

Three forms of linear interpolation are routinely implemented in geographical information science, by interpolating between measurements made at the endpoints of a line, the vertices of a triangle, and the vertices of a rectangle (bilinear interpolation). Assuming the linear form of interpolation to be correct, we study the propagation of error when measurement error variances and covariances are known for the samples at the vertices of these geometric objects. We derive prediction error variances associated with interpolated values at generic points in the above objects, as well as expected (average) prediction error variances over random locations in these objects. We also place all the three variants of linear interpolation mentioned above within a geostatistical framework, and illustrate that they can be seen as particular cases of Universal Kriging (UK). We demonstrate that different definitions of measurement error in UK lead to different UK variants that, for particular expected profiles or surfaces (drift models), yield weights and predictions identical with the interpolation methods considered above, but produce fundamentally different (yet equally plausible from a pure data standpoint) prediction error variances.     

Estimation of pH optima and tolerances of diatoms in lake sediments by the methods of weighted averaging,least squares and maximum likelihood,and their use for the prediction of lake acidity

Ecological optima and tolerances with respect to autumn pH were estimated for 63 diatom taxa in 47 Finnish lakes. The methods used were weighted averaging (WA), least squares (LS) and maximum likelihood (ML), the two latter methods assuming the Gaussian response model.WA produces optimum estimates which are necessarily within the observed lake pH range, whereas there is no such restriction in ML and LS. When the most extreme estimates of ML and LS were excluded, a reasonably close agreement among the results of different estimation methods was observed. When the species with unrealistic optima were excluded, the tolerance estimates were also rather similar, although the ML estimates were systematically greater.The parameter estimates were used to predict the autumn pH of 34 other lakes by weighted averaging. The ML and LS estimates including the extreme optima produced inferior predictions. A good prediction was obtained, however, when prediction with these estimates was additionally scaled with inverse squared tolerances, or when the extreme values were removed (censored). Tolerance downweighting was perhaps more efficient, and when it was used, no additional improvement was gained by censoring. The WA estimates produced good predictions without any manipulations, but these predictions tended to be biased towards the centroid of the observed range of pH values.At best, the average bias in prediction, as measured by mean difference between predicted and observed pH, was 0.082 pH units and the standard deviation of the differences, measuring the average random prediction error, was 0.256 pH units.     

USE OF THE KALMAN FILTER FOR MULTIVARIATE CALIBRATION IN A REAL SYSTEM AND ITS COMPARISON WITH CLS AND PURE COMPONENT CALIBRATION METHODS

The usefulness of the Kalman filter as an algorithm for calibration in a real system is shown. Results arecompared with classical least squares and pure component calibration. The prediction of four prioritypollutant chlorophenols in binary, ternary and quaternary mixtures was also carried out by Kalmanfiltering. The condition number, standard deviation and prediction error have been employed to choosethe most suitable wavelength range. Comparison of the standard error of prediction in the validation setshows significant differences between the evaluated chlorophenols, the best results being obtained withKalman multivariate calibration.     

On Blind Tests and Spatial Prediction Models

This contribution discusses the usage of blind tests, BT, to cross-validate and interpret the results of predictions by statistical models applied to spatial databases. Models such as Bayesian probability, empirical likelihood ratio, fuzzy sets, or neural networks were and are being applied to identify areas likely to contain events such as undiscovered mineral resources, zones of high natural hazard, or sites with high potential environmental impact. By processing the information in a spatial database, the models establish the relationships between the distribution of known events and their contextual settings, described by both thematic and continuous data layers. The relationships are to locate situations where similar events are likely to occur. Maps of predicted relative resource potential or of relative hazard/impact levels are generated. They consist of relative values that need careful quantitative scrutiny to be interpreted for taking decisions on further action in exploration or on hazard/impact mitigation and avoidance. The only meaning of such relative values is their rank. Obviously, to assess the reliability of the predicted ranks, tests are indispensable. This is also a consequence of the impracticality of waiting for the future to reveal the goodness of our prediction. During the past decade only a few attempts have been made by some researchers to cross-validate the results of spatial predictions. Furthermore, assumptions and applications of cross-validations differ considerably in a number of recent case studies. A perspective for all such experiments is provided using two specific examples, one in mineral exploration and the other in landslide hazard, to answer the fundamental question: how good is my prediction?     

极地冰盖物质平衡的最新进展与未来挑战

准确地探明冰盖物质平衡状况,对于研究全球变暖背景下海平面变化具有重要的意义,自IPCC AR4(政府间气候变化专门委员会第四次报告)以来,极地冰盖物质平衡的研究取得了很大进展。本文总结并对比了用卫星测高(雷达测高和激光测高)、物质收支测量和重力测量等方法得到的冰盖物质平衡评估结果,综述了冰盖数值模拟研究在预测冰盖未来的变化趋势以及由此对海平面造成的影响等方面取得的进展,并立足于中国当前的极地冰盖物质平衡研究现状,提出了该研究所面临的挑战。     

近20年来黄河流域植被覆盖变化分析

利用1982～1999年AVHRR-NDVI数据和对应年份黄河流域气象观测数据，通过计算、分析春季、夏汛及伏秋黄河流域NDVI距平值和湿润指数距平值的年际变化，得出了20世纪80年代至90年代初黄河流域气候相对湿润，90年代中后期相对干旱，植被覆盖状况总体一直处于上升趋势的结论，并评估了黄河流域近20年来生态保护和建设工作成效。     

Tidal gravity in Britain: tidal loading and the spatial distribution of the marine tide

Summary. Tidal gravity measurements have been made at six sites in Britain with two nulled LaCoste and Romberg Earth tide gravitymeters. The M ₂ observations from these and two further sites are compared with calculations of the tidal loading from the seas around the British Isles and the major oceans. Models of the M ₂ marine tides are convolved with Green's functions for appropriate radially stratified Earth models. The differences between the M ₂ observations and the theoretical calculations are less than 0.6 μ gals and it is shown that these differences contain further information concerning the errors in the marine tide models. The M ₂ marine tides on the north-west European continental shelf are reasonably well known and this allows a useful test of the feasibility of using tidal gravity measurements for the inverse ocean tide problem in areas where the ocean tides are less well known. The differential gravity loading signal between pairs of gravity stations is shown to be important for considerations of the uniqueness and accuracy of the inverse problem. M ₂ tidal gravity loading maps for the British Isles and Europe have been produced which are of use in making corrections to various geodetic measurements.     

中国地理研究所(1940—1949年)纪略

本文简述了前中国地理研究所的十年(1940—1949年)历史,尤着重于其研究成果的介绍。     

1978-2006年甘肃产业结构演进分析

以1978-2006年统计数据为基础,采用产业经济学、计量经济学和统计学的相关方法,对甘肃省改革开放以来的产业结构演进进行了定量分析,对其与同期全国产业结构演进进行了比较。研究结果表明,1978年以来,甘肃与全国产业结构演进存在差异,主要表现为:甘肃第二产业比重明显偏低,第三产业比重偏高;甘肃产业产值比重与就业比重不均衡度明显高于全国,近年有扩大趋势;甘肃的产业结构转换速度缓慢,且主要依赖第三产业的推动,转换方向不尽合理;甘肃经济增长结构效应在减弱,增长结构中夕阳产业比重高,比较优势产业竞争力有所提高。