国际地磁参考场在我国地磁基础研究中的应用

国际地磁参考场资料在我国得到广泛应用。利用国际地磁参考场资料，我国学者研究了高斯分析、地球磁场模型及其源场可能位置、重磁关系、核幔耦合、地磁场能量、地球非偶极子磁场西向漂移等。在绘制中国地磁等值图中也利用了某些国际地磁参考场资料。     

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)。     

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.     

地震CT勘探原理及其在公路隧道病害诊断中的应用

地震CT勘探是一种新的地球物理方法。具有分辨率高、可靠性强、信息量大、图象直观的特点。可以广泛地用于线路、场地、隧道、边坡等项目的工程地质勘查和病害诊断。在元磨高速公路芭蕉箐隧道的地质病害诊断中应用地震CT进行勘探,取得了良好的效果。     

户县麦饭石的开发利用研究

文中指出了矿物在农业应用中的重要性，开发研制矿物饲料有着非常巨大的经济效益和社会效益。应用先进的分析、测试设备和手段，对产于秦岭北缘的户县麦饭石的矿物成分、化学成分、微量元素、稀土元素等进行了分析测试；并对该麦饭石的溶解性、吸附性等做了大量的实验研究，在综合研究基础上，得出结论：户县麦饭石非常适于作为矿物饲料。     

土壤水力性质确定方法研究进展

介绍了确定土壤水力性质的各种直接方法(包括实验室方法和田间方法两大类)和间接方法如土壤转换函数方法、分形方法、形态学方法、数值反演方法和经验公式法等的研究进展和现状,指出了它们各自的优点和存在的不足.认为要不断地引入新的实验技术和改进测定设备,并把估计土壤水力性质的各种理论方法及实验信息有机地结合起来进行综合研究,以扩大它们的适用范围和提高预测精度.     

拓展国际合作的视野--出席第23届IUGG大会有感

第23届IUGG大会一个突出的特点就是学科间的交叉和融合，充分反映了新世纪地球科学以实现全球变化的预测为目标，进行多学科综合研究的发展趋势。文章从IUGG内部跨学科的合作研究，IUGG与国际科联(ICSU)各专业委员会之间的合作交流，以及IUGG与政府间组织和其他国际机构的合作三个层面，简要介绍了IUGG在全球范围内开展国际合作研究的概况。在此基础上，结合我国的实际，就拓展国际合作领域，提高我国地球科学研究水平，扩大我国的国际影响等提出了相应的建议。     

关于加强地震预报基础研究的思考

回顾了国内外地震预报研究40年的经历和现状，指出几十年来所取得的科学进展与突破地震预报的科学目标之间还有相当的距离。文章分析了地震预测中的科学难点，提出了加强地震预测基础研究的重要性和必要性，并指出了加强地震预报基础研究的若干科学问题。     

古代生物分子在第四纪研究中的应用

从第四纪化石和沉积物中获得的古代生物分子为第四纪研究者提供了丰富和独特的有关古代生物、遗传和古环境信息的定量和高分辨率的数据.过去10多年的研究证实来自第四纪材料中的各种古代生物分子的分离、鉴定和应用的能力在不断增加.文章总结了古代生物分子在第四纪研究中的最新进展,主要包括以下几个方面的内容:1)不同类型的古代生物分子在地质体中的保存和降解;2)古DNA和古蛋白序列中的生物遗传学信息;3)单体分子同位素与第四纪古环境和古气候研究;4)建于古代生物分子水平上的第四纪年代学.作者预见对第四纪地层中的原位和分散保存的古代生物分子的研究将在广度上以多分子综合研究而深度上与单体分子同位素技术相结合,为第四纪科学家们提供大量解决地质学和演化生物学问题的高精度数据.随着地球化学和分子生物学技术的不断改进以及人们对古代生物分子的降解过程和机制的进一步理解,对古代生物分子的研究无疑将进一步促进和推动第四纪科学研究的发展.