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.     

长江三峡狮子口重力滑动构造

围绕着长江三峡库处区狮子口ＮＮＷ向线性影像带的构造性及其地壳稳定性评价问题进行了专题研究，以区域地质调查为基础，运用构造解析方法，采用多学科，多手段的综合研究，确认该影像带影像特征最明显的地段乃是一个滑褶型多层式得力滑动构造，本文还分析了该系统形成的介质条件，斜坡构造及动力环境。     

Fault geometry and mechanics of marly carbonate multilayers: An integrated field and laboratory study from the Northern Apennines,Italy

Sealing layers are often represented by sedimentary sequences characterized by alternating strong and weak lithologies. When involved in faulting processes, these mechanically heterogeneous multilayers develop complex fault geometries. Here we investigate fault initiation and evolution within a mechanical multilayer by integrating field observations and rock deformation experiments. Faults initiate with a staircase trajectory that partially reflects the mechanical properties of the involved lithologies, as suggested by our deformation experiments. However, some faults initiating at low angles in calcite-rich layers (θ_i = 5°–20°) and at high angles in clay-rich layers (θ_i = 45°–86°) indicate the important role of structural inheritance at the onset of faulting. With increasing displacement, faults develop well-organized fault cores characterized by a marly, foliated matrix embedding fragments of limestone. The angles of fault reactivation, which concentrate between 30° and 60°, are consistent with the low friction coefficient measured during our experiments on marls (μ_s = 0.39), indicating that clay minerals exert a main control on fault mechanics. Moreover, our integrated analysis suggests that fracturing and faulting are the main mechanisms allowing fluid circulation within the low-permeability multilayer, and that its sealing integrity can be compromised only by the activity of larger faults cutting across its entire thickness.     

卫星遥感接收数据的管理与软件开发

卫星遥感接收数据是遥感影像应用的重要数据来源,因此对特殊格式的海量接收数据的存储和管理成为卫星遥感应用的重要环节。采用多层存储模式对数据分类、分级存储,建立空间数据库管理空间数据和属性数据。基于ArcEngine开发技术建立卫星接收数据管理平台,实现空间数据的快速查询和属性数据的自动入库等高效管理功能。     

水库群优化调度函数的人工神经网络方法研究

提出了研究水库群优化调度函数的人工神经网络方法,并探讨了神经网络的训练参数、训练方法和训练样本的改变对网络训练和应用效果的影响。实例研究表明,模型及其算法是可行的、有效的。     

多通道地下水监测技术应用示范

多通道地下水监测技术能够大幅度降低地下水监测成本。多通道监测井成井井管是采用HDPE材质挤出若干通道的连续管材,在每个通道指定位置加工窗口,对应相应的地下水监测层位,并设计合理的填砾止水厚度。根据多通道地下水监测井特点,研制新型的止水材料。采用该种地下水监测技术,先后在北京、天津、甘肃等地建立了地下水监测示范工程。与传统地下水监测技术相比,节约了占地面积、减少了钻探进尺,与国外CMT地下水监测技术对比,适用范围更广,建井成本更低。     

从高密度电阻率法数据中抽取电测深曲线进行解释

对于碳酸盐岩地层中的多层岩溶、溶洞洞高较小或顺层岩溶,直接从高密度电阻率拟断面图和反演电阻率断面图上难以将其区分。通过从高密度电法数据中抽取电测深曲线,对一系列测点的电测深视电阻率曲线进行解释,同时结合其视电阻率拟断面图和反演电阻率断面图作出推断,能有效地将上述岩溶进行区分。在湖南省某高速公路跨线桥墩台桩基工程基础勘探中的实践表明,使用该方法可获得较好的地质解释效果。     

非饱和土地基中复合多层波阻板对S波的隔离效应

基于弹性波在非饱和多孔介质与单相弹性介质中的传播理论,考虑在非饱和土地基中设置一定厚度的复合多层波阻板（复合多层波阻板以3层为例）,利用Helmholtz矢量分解定理,推导了非饱和土地基中S波通过复合多层波阻板的透射、反射振幅比的解析解。通过数值算例,分析了层间波阻板剪切模量和密度等物理力学参数对非饱和土地基中S波通过复合多层波阻板时传播特性的影响规律。结果表明：复合多层波阻板中层间波阻板材料的剪切模量和密度对透反射系数影响显著。复合多层波阻板是一种有效的隔振屏障,严格控制层间波阻板的剪切模量和密度可以获得最佳隔振效果,这为复合多层波阻板在地基振动控制领域中的应用提供理论指导。     

InFOCμS Hard X-ray Imaging Telescope

InFOCμS is a new generation balloon-borne hard X-ray telescope with focusing optics and spectroscopy. We had a successful 22.5-hour flight from Fort Sumner, NM on September 16,17, 2004. In this paper, we present the performance of the hard X-ray telescope, which consists of a depth-graded platinum/carbon multilayer mirror and a CdZnTe detector. The telescope has an effective area of 49 cm² at 30 keV, an angular resolution of 2.4 arcmin (HPD), and a field of view of 11 arcmin (FWHM) depending on energies. The CdZnTe detector is configured with a 12 × 12 segmented array of detector pixels. The pixels are 2 mm square, and are placed on 2.1 mm centers. An averaged energy resolution is 4.4 keV at 60 keV and its standard deviation is 0.36 keV over 128 pixels. The detector is surrounded by a 3-cm thick CsI anti coincidence shield to reduce background from particles and photons not incident along the mirror focal direction. The inflight background is 2.9 × 10⁻⁴ cts cm⁻² sec⁻¹ keV⁻¹ in the 20–50 keV band.