南北带北段磁性构造特征和地震活动的关系

利用航磁资料研究了南北带北段的磁属性构造，反演了该区居里等温面的埋藏深度，推断了不同深度断裂的分布情况，进南昌讨论了地震与深部背景的关系。     

地震预报思路的再讨论

文中回顾了1974年提出的“块、带、源、兆、触、报”六字预报思路，并基于近20年来的研究对此进行了补充和深化。     

新疆且末县吐孜敦古地震形变带及其年代问题

新疆且末县拟在吐拉乡阿尔金活动断裂带上修建水库。水库近场区内沿阿尔金活动断裂存在一条古地震破裂形变带。为了对水库进行安全性评价 ,采用地貌风化剥蚀法确定了古地震形变带的形成年代。该次古地震事件的发生时间大约距今 4 0 0年前     

南北地震带强震复发间隔的估计

通过对南北地震带各主要断裂带历史强震的时空特点研究 ,试图寻找出带内各主要构造带强震的复发和填充特征 ,并在此基础上研究其差异性 ,对未来各带发生强震的危险性作出估计     

天山西部中山带积雪变化趋势与气温和降水的关系——以巩乃斯河谷为例

根据位于巩乃斯河谷的天山积雪雪崩研究站近30年来的年最大雪深、月平均气温、月降水量观测记录，用平均差值法、最小二乘法、自回归滑动平均法检验了天山西部中山带积雪、冷季降水、冷季平均气温的变化趋势，结果表明，天山西部中山带积雪呈增加趋势，近30年来年平均增加1.43%，与青藏高原、南极大陆及格陵兰冰盖表面积雪积累增加相一致。天山西部中山带冷季气温和降水的变化趋势也是增加的，其中冷季降水平年平均增加0．12％，而冷季气温升高了0．8℃，积雪与冷季气温之间存在着弱的负相关关系，而与冷季降水呈显著的正相关关系。积雪的增加主要是因为气候变暖引起的冷季降水的增加对积雪增加的贡献大于由于冷季气温升高而造成积雪减少的贡献的结果。     

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.     

青藏高原北部可可西里狮头山含硬玉岩类的基本特征及地质意义

描述了可可西里山南狮头山含硬玉岩类的岩石学、矿物学特征。含硬玉岩类的原岩为辉长岩，围岩为石炭—二叠系。由于变质作用不彻底，保留有原岩的矿物组合。典型的高压变质矿物组合为：钠长石 硬玉 霓石 蓝闪石 绿帘石 绿泥石。硬玉SiO2、FeO偏低，Al2O3、Na2O明显偏高，变质矿物组合中以富钠矿物为主，缺少石英，与国内外含硬玉岩类的原岩成分、变质矿物组合均不相同，是一种新的高压低温硬玉岩类。狮头山高压变质带向西延至若拉岗日、大横山一带，与北侧的西金乌兰—金沙江板块缝合带(西段)平行产出，以此推测缝合带南侧的羌北—昌都板块向北消减于巴颜喀拉板块之下。     

湖南郴州-邵阳走滑型构造岩浆岩带及其控矿意义

在总结郴州—邵阳走滑型构造岩浆岩带基本特征和活动历史的基础上，对其形成机制和成矿作用进行了探讨．认为该走滑型构造岩浆岩带由隐伏的基底断裂带、侵入岩浆岩带和盖层中断续分布的北西向褶皱、冲断层组成，是板块会聚时两板块凸出部分相接触形成的应力集中带。它不仅是地幔长期隆起(尤其是晚古生代)地带，而且是一条重要的控岩控矿控制岩相的活动带。其中走滑型构造—岩浆岩环境下的锡、钨、铜、铅、锌、金矿床主要与燕山期壳源改造—重融型、壳幔源混熔型中酸性、酸性岩浆岩有关。     

义敦成矿带铜银铅锌锡矿产资源调查评价进展与潜力

义敦成矿带地处独特的大地构造部位，经历了复杂的地质构造演化和强烈的岩浆活动，成矿条件优越，矿产资源丰富。1999年实施国土资源地质大调查以来，相继发现了普朗、松诺、卓玛斑岩铜矿；砂西、热朗泽、夏隆等银铅锌矿；热隆、脚根玛锡矿；打马池觉铜金矿等一批具有重要找矿前景的矿床(点)。该地区矿产资源勘查工作程度低，蕴藏着较大的找矿潜力，有望成为国家级重要的有色及贵金属矿产勘查和开发基地。