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81.
Three Alkali-Rich Intrusive Rock Belts Newly Discovered in the Mt. Kunlun-Mt. Altun Region, Xinjiang, China 总被引:1,自引:0,他引:1
The newly discovered three alkali-rich intrusive rock belts in the Mt. Kunlun Mt.Altun region of southern Xinjiang are the Lapeiquan-Yitunbulak alkali-rich intrusive rock belt,the Gez-Taxkorgan alkali-rich intrusive rock belt and the Beilisai-Abulash alkali-rich intrusive rock belt. The former two belts were formed during the Yanshanian period, and the third one was formed during the Himalayan period, which is the youngest alkali-rich intrusive rock belt in China. The discovery of the alkali-rich intrusive rock belts is of great significance in shedding light on the history of tectono-magmatic activities in this region. 相似文献
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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 总被引:12,自引:9,他引:12
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。 相似文献
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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. 相似文献
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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. 相似文献
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世界斑岩铜矿主要产于中生代一新生代环太平洋带、古特提斯带和古生代中亚—蒙古带,因为上述3带为聚合板块集中分布地区。中国西藏集中了金沙江聚合带、雅鲁藏布江聚合带和怒江—班公错聚合带,为世界上聚合板块最发育地区之一,具有较长的大洋板块俯冲和陆—陆碰撞的造山历史,构造—花岗质岩浆十分发育,其中深源高侵位的花岗质斑岩分布广泛,对于形成斑岩铜矿和其他相关矿床十分有利,为找矿评价斑岩铜(金)矿很有前景的地区。笔者借鉴世界和中国评价斑岩铜矿的经验,同时收集了西藏近年来找寻评价斑岩铜矿有关的地质资料,对西藏斑岩铜矿的前景进行了展望。 相似文献