MAPGIS管网开发平台的设计

设计了一个通用的管线信息系统开发平台。该开发平台构筑于大型GIS基础软件MAPGIS之上，具有完备的数据模型，强大的数据包容能力。采用多层次体系结构，包含网络数据管理与网络分析、管网工作区管理、专业管网工作区管理、管网工程管理、管网实用服务工具包、管网管理类库和控件库等多个模块。该开发平台同时支持API和组件接口，二次开发便利灵活，可以较好地满足管网应用系统的。在该平台基础上已开发出多个成功的管网信息系统，证明它具有广泛的应用前景。     

Ordovician Graptolite Rhabdosome Complication and Its Implications on Sea Level Changes

A total of four times of rhabdosome complication events, i.e., the lateral branching of graptolite stipes during the Late Middle Ordovician, the secondary branching of graptolite stipes at the earliest Upper Ordovician, the early Qiantangjiangian of Upper Ordovician and the middle Qiantangjiangian, respectively, is discussed in this paper. These events and other adaptation events demonstrate close relationships between a diverse graptolite fauna and sea level changes, and consequently can be employed to study sea level fluctuations. It is safe to conclude that the complication of rhabdosome started at the maximum flooding surface (MFS) and terminated at the beginning of regression.     

GIS支持下青海湖地区草地蝗虫发生的地形分析

草地蝗虫发生的地形分析是建立草地蝗虫发生预报模型的基础，以青海湖地区为实验区，在Arc/Info和ArcView地理信息系统的支持下，进行草地蝗虫发生与各地形变量（包括海拔高度、坡度与坡向）的叠置分析，提取草地蝗虫发生的地形信息数据库，然后，分别采用T－检验（对连续变量－海拔高度和坡度）和卡方（Chisquare)检验（对类变量－坡向类型）进行各地形变量对草地蝗虫发生的差异显著性检验，结果表明，海拔高度和坡度对草地蝗虫发生的影响极为显著（显著性水平p=0.000)，而坡向地草地蝗虫发生的影响不是特别明显（显著性水平p=0.039)。     

基于GIS的滑坡CF多元回归模型及其应用

目前基于GIS滑坡变形失稳危险性评价方法均有各自的局限性。本文在基于数据的数学统计模型的基础上提出CF多元回归模型。通过将滑坡确定性稳定系数与回归模型的融合，在一定程度以解决了滑坡评价过程中影响因子的选择和量化的问题，有利于建立准确的滑坡分析模型。最后，将模型应用于云南小江流域，进行了该区的滑坡空间分布及稳定性分析。     

Palaeolimnology of Lake Piene-Kuuppalanlampi (Kurkijoki, Karelian Republic, Russia): isolation history, lake ecosystem development and long-term agricultural impact

The post-glacial history of Lake Pieni-Kuuppalanlampi, western Lake Ladoga region, was studied by means of stratigraphic pollen and diatom analyses. Diatoms were analysed to track the isolation history of the basin and the limnological effects of the early land-use phases indicated by pollen analysis. Chrysophycean stomatocysts and Isoëtes spores were also employed in the limnological reconstructions. Sediment dating was provided by six conventional radiocarbon dates.The lower part of the 370-cm long sediment sequence represents early Holocene, large lake conditions: the (freshwater) Yoldia and Ancylus stages of the Baltic basin, with a short-term lagoonal or isolation phase at the end of Yoldia. The basin was isolated due to Ancylus lake regression at 9785 cal B.P. For the small-lake sequence (0–250 cm) we used diatom inferences (WA-method) for hindcasting water chemistry. The post-isolation limnology of Pieni-Kuuppalanlampi reflects the development of vegetation on its small hill-top catchment. In its early development, the lake was mesotrophic, but became more acidic (pH about 6) and oligotrophic after the decline of temperate hardwood trees and the spread of spruce to the area after around 5000 B.P. The lake ecosystem appears to have reacted sensitively to agricultural land-use in the catchment from AD 400–800 onwards: inferred total phosphorus levels and pH both rise during these periods.     

Soulèvement et plissement tectoniques révélés par analyse mathématique empirique de profils longitudinaux de rivières : un cas à TaiwanEmpirical mathematical analysis of longitudinal river profiles reveals tectonic uplift and folding: a case in Taiwan

We analyse longitudinal river profiles in southwestern Taiwan. As all necessary data are not available, a physical modelling of river erosion would be subject to large uncertainties. We thus shortcut this modelling and adopt simple empirical exponential equations giving riverbed elevation as a function of downstream distance. We identify a positive altimetric anomaly, which reveals active uplift of an anticline at the front of the fold-and-thrust belt. To cite this article: J. Angelier, R.-F. Chen, C. R. Geoscience 334 (2002) 1103–1111.     

Use of Noise to Augment Training Data: A Neural Network Method of Mineral–Potential Mapping in Regions of Limited Known Deposit Examples

One of the main factors that affects the performance of MLP neural networks trained using the backpropagation algorithm in mineral-potential mapping isthe paucity of deposit relative to barren training patterns. To overcome this problem, random noise is added to the original training patterns in order to create additional synthetic deposit training data. Experiments on the effect of the number of deposits available for training in the Kalgoorlie Terrane orogenic gold province show that both the classification performance of a trained network and the quality of the resultant prospectivity map increasesignificantly with increased numbers of deposit patterns. Experiments are conducted to determine the optimum amount of noise using both uniform and normally distributed random noise. Through the addition of noise to the original deposit training data, the number of deposit training patterns is increased from approximately 50 to 1000. The percentage of correct classifications significantly improves for the independent test set as well as for deposit patterns in the test set. For example, using ±40% uniform random noise, the test-set classification performance increases from 67.9% and 68.0% to 72.8% and 77.1% (for test-set overall and test-set deposit patterns, respectively). Indices for the quality of the resultant prospectivity map, (i.e. D/A, D × (D/A), where D is the percentage of deposits and A is the percentage of the total area for the highest prospectivity map-class, and area under an ROC curve) also increase from 8.2, 105, 0.79 to 17.9, 226, 0.87, respectively. Increasing the size of the training-stop data set results in a further increase in classification performance to 73.5%, 77.4%, 14.7, 296, 0.87 for test-set overall and test-set deposit patterns, D/A, D × (D/A), and area under the ROC curve, respectively.     

Use of Fuzzy Membership Input Layers to Combine Subjective Geological Knowledge and Empirical Data in a Neural Network Method for Mineral-Potential Mapping

Use of GIS layers, in which the cell values represent fuzzy membership variables, is an effective method of combining subjective geological knowledge with empirical data in a neural network approach to mineral-prospectivity mapping. In this study, multilayer perceptron (MLP), neural networks are used to combine up to 17 regional exploration variables to predict the potential for orogenic gold deposits in the form of prospectivity maps in the Archean Kalgoorlie Terrane of Western Australia. Two types of fuzzy membership layers are used. In the first type of layer, the statistical relationships between known gold deposits and variables in the GIS thematic layer are used to determine fuzzy membership values. For example, GIS layers depicting solid geology and rock-type combinations of categorical data at the nearest lithological boundary for each cell are converted to fuzzy membership layers representing favorable lithologies and favorable lithological boundaries, respectively. This type of fuzzy-membership input is a useful alternative to the 1-of-N coding used for categorical inputs, particularly if there are a large number of classes. Rheological contrast at lithological boundaries is modeled using a second type of fuzzy membership layer, in which the assignment of fuzzy membership value, although based on geological field data, is subjective. The methods used here could be applied to a large range of subjective data (e.g., favorability of tectonic environment, host stratigraphy, or reactivation along major faults) currently used in regional exploration programs, but which normally would not be included as inputs in an empirical neural network approach.     

合肥市耕地和粮食可持续发展研究

收集1980～1999年合肥市耕地、人口、粮食等资料，定量分析在城市化快速发展下耕地的数量、质量变化和耕地减少的形式以及人口、粮食的变化，并用回归法分析它们的变化趋势。研究认为，在2005，2010年合肥市食物保障能力分别为97％和95％，对粮食生产与其影响因素进行了灰色关联分析，提出提高粮食产量的对策和实现途径。     

PLS法与隧道围岩稳定性分类

围岩稳定性是隧道工程支护设计的基本参数,采用偏最小二乘回归法,综合考虑多因变量影响因素,对隧道围岩稳定性分类进行回归建模,并取得较好效果.