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.     

智能交通系统中的公交车辆指挥调度体系结构

该文阐述公交智能指挥调度系统总体框架，结合智能交通系统ITS(Intelligent Transport Systems)对公交智能化调度的逻辑结构和物理结构要求，分析公交车辆智能化调度系统结构体系及其模型化，探讨智能调度策略和调度机理。根据该系统总体设计框架构思，了解系统各功能间的相互关系，优化公交车辆运营管理模式，以改善现有公交系统的管理水平以及运营效率，为公交指挥调度系统的完善、提高提供可靠技术基础。     

多维植被信息系统及其应用前景

3S(地理信息系统GIS、遥感RS、全球定位系统GPS)及其相关技术的发展，使得植被信息系统的构建和应用成为可能。早期的植被图没有涉及到高度维和时间维，其应用受到很大的限制。因此有必要建立一种基于时空的多维植被信息系统，它的组成包括地理信息系统GIS、数据处理模块DPM、数据存取模块DAM、植被分析模块VAM和交互显示模块IDM，可用于植被的时空分析、三维景观显示、植被—地形—气候关系研究以及植被综合管理等方面，特别适合于山地植被的研究。多维植被信息系统具备立体直观的用户友好界面和强大的时空数据处理能力，并可通过数据库和网络进行资源共享，使植被研究和管理自动化、无纸化，其应用前景广阔。     

多右端非对称位移方程组的GMRES种子投影方法

考虑用GMRES方法求解多右端非对称位移方程组(A-σjI)x^(j)=b^(j)，1≤j≤p。基于Smith的求解多右端方程组的种子投影思想，提出了求解上述位移方程组的GMRES种子投影方法，利用种子方程组产生的Krylov子空间来求近似解。本文给出了近似解的误差界，最后数值结果显示了该方法的有效性。     

Identification of soil degradation during earthquake excitations by Bayesian inference

A Bayesian inference approach is introduced to identify soil degradation behaviours at four downhole array sites. The approach of inference is based on a parametric time‐varying infinite impulse response filter model. The approach is shown to be adaptive to the changes of filter parameters and noise amplitudes. Four sites, including the Lotung (Taiwan), Chiba (Japan), Garner Valley (California), and Treasure Island (California) sites with downhole seismic arrays are analysed. Our results show two major types of soil degradation behaviour: the well‐known strain‐dependent softening, and reduction in stiffness that is not instantaneously recoverable. It is also found that both types of soil degradation are more pronounced in sandy soils than in clayey soils. The mechanism for the second type of soil degradation is not yet clear to the authors and suggested to be further studied. Copyright © 2003 John Wiley & Sons, Ltd.     

Seismic risk assessments and GIS technology: applications to infrastructures in the Friuli–Venezia Giulia region (NE Italy)

This paper illustrates the seismic risk preliminary estimates of two different groups of structures located on the territory of the Friuli–Venezia Giulia region (NE Italy) : the first group includes some special industrial plants, and the second group includes bridges and tunnels belonging to the regional highway network. The part of the study on special industrial plants tries to evaluate the degree of expected damage, taking into account their structural typology and ground shaking expressed in terms of macroseismic intensity. The second part of the study is an application of the HAZUS methodology to the tunnels and bridges of a highway network: the combination of expected ground shaking and the construction characteristics lead to very different risk levels, especially when considering the bridges. The resulting damage levels to bridges and tunnels are still only indicative because of the fragility curves used in the evaluations: they were developed for existing bridge and tunnel structural typologies in the U.S.A. Moreover, both examples show the power of GIS technology in storing, elaborating, and mapping spatial data. Copyright © 2003 John Wiley & Sons, Ltd.     

论层序地层学与含油气系统在油气勘探中的联系——以鄂尔多斯中生代盆地为例

虽然层序地层学与含油气系统理论的各自研究对象和研究方法不同，但由于层序地层学研究对象(沉积岩)是含油气系统研究对象(油气)的载体，二者可以由含油气盆地分析有机的结合起来。层序地层分析包含了对含油气系统的地质要素及成藏作用载体的分析，因而沉积层序的组成单元与含油气系统的地质要素有必然的联系：在一个沉积盆地的数个沉积层序中，成熟烃源岩往往是地史中具一定埋深、分布广、厚度大、有机质含量高的凝缩层，这个凝缩层往往是一个构造超层序的最大海(湖)泛面；储集岩往往是成熟烃源岩之上层序的低水位体系域或紧邻成熟烃源岩的高水位体系域；有效盖层为储集岩之上层序的水进体系域及凝缩层；成熟烃源岩之上的沉积层序为上覆岩层；低水位体系域储集岩有可能沿上倾方向尖灭，被层序界面及其上层序的水进体系域岩性圈闭；除构造裂缝外，低水位体系域下切谷可作为油气向上运移通道；一个含油气系统往往跨越不同的沉积层序甚至构造超层序。     

东北大部旱情缓解 粤闽局地暴雨成灾──1997年5月

东北大部旱情缓解粤闽局地暴雨成灾—１９９７年５月—徐良炎（国家气候中心，北京１０００８１）５月份，东北大部、华北北部及黄淮等地普降喜雨，旱情缓解；西北东部、华北西部等地降水偏少，旱情持续或发展。南方大部地区雨水比较调匀，无大范围旱涝发生，但华南局地遭...     

数字化地震遥测台网不间断供电系统研制

本文介绍一种适用于数字化遥测地震台网的不间断供电系统，它具有交直流不间断切换，输出满足数据采集系统及数据传输设备所需的各种电压要求，并能对备份蓄电池自动恒流、恒压转换充电及过放电保护，冗余量大、可靠性高。解决了无人值守遥测地震台的供电问题。对其它数字设备也有广泛的应用价值。