A study on the early-warning technique concerning debris flow disasters     

ZHOU Jinxing  Wang Lixian  XIE Baoyuan  FEI Shimin  Wang Xilin 《地理学报(英文版)》2002,12(3)

According to the principle of the eruption of debris flows, the new torrent classification techniques are brought forward. The torrent there can be divided into 4 types such as the debris flow torrent with high destructive strength, the debris flow torrent, high sand-carrying capacity flush flood torrent and common flush flood by the techniques. In this paper, the classification indices system and the quantitative rating methods are presented. Based on torrent classification, debris flow torrent hazard zone mapping techniques by which the debris flow disaster early-warning object can be ascertained accurately are identified. The key techniques of building the debris flow disaster neural network (NN)real time forecasting model are given detailed explanations in this paper, including the determination of neural node at the input layer, the output layer and the implicit layer, the construction of knowledge source and the initial weight value and so on. With this technique, the debris flow disaster real-time forecasting neural network model is built according to the rainfall features of the historical debris flow disasters, which includes multiple rain factors such as rainfall of the disaster day, the rainfall of 15 days before the disaster day, the maximal rate of rainfall in one hour and ten minutes. It can forecast the probability, critical rainfall of eruption of the debris flows, through the real-time rainfall monitoring or weather forecasting. Based on the torrent classification and hazard zone mapping, combined with rainfall monitoring in the rainy season and real-time forecasting models, the debris flow disaster early-warning system is built. In this system, the GIS technique, the advanced international software and hardware are applied, which makes the system′s performance steady with good expansibility. The system is a visual information system that serves management and decision-making, which can facilitate timely inspect of the variation of the torrent type and hazardous zone, the torrent management, the early-warning of disasters and the disaster reduction and prevention.  相似文献   

Competitive Adjustment and Advancement in Global Commodity Chains II: The Case of the Singapore Garment Industry     

Leo van Grunsven  & Floor Smakman 《Singapore journal of tropical geography》2002,23(1):70-92

This is the second part of a contribution to the debate on the possibilities of leveraging economic globalisation — through incorporation in international production networks and global commodity chains (GCCs) — as a strategy for developing countries to industrialise and advance their position in the world economy. In the first part, we analysed the experience of the East Asian apparel industry and addressed the issues of sustaining positions, upgrading to more rewarding roles, and advancing to less dependent positions within production networks and GCCs. We developed an analytical framework at both the firm and industry levels, and subsequently identified alternative firm- and industry-level strategies and trajectories. The present paper deals with these issues in the context of the Singapore apparel industry. Based on extensive empirical research, we demonstrate that although the East Asian experience of upgrading and repositioning within the GCC is to some extent emulated in the case of the Singapore apparel industry, the outcomes have been less favourable in terms of the depth, extent and strength of these trajectories. The differing outcomes can be explained in terms of different (systemic) conditions in the Singapore business environment, including the agency of local players, the geography of sourcing networks, and the role of the state and prevailing business attitudes. Our conclusions merit continued attention in both research and policy circles on the development of capabilities at the firm level, and the role of local business and institutional environments in local industry development processes under globalisation.  相似文献   

Use of Noise to Augment Training Data: A Neural Network Method of Mineral–Potential Mapping in Regions of Limited Known Deposit Examples     

Warick M. Brown  Tamás D. Gedeon  David I. Groves 《Natural Resources Research》2003,12(2):141-152

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   

Use of Fuzzy Membership Input Layers to Combine Subjective Geological Knowledge and Empirical Data in a Neural Network Method for Mineral-Potential Mapping   总被引：3，自引：0，他引：3  

Brown  Warick  Groves  David  Gedeon  Tamás 《Natural Resources Research》2003,12(3):183-200

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   

企业网络发育程度与区域创新能力研究   总被引：10，自引：0，他引：10  

文嫮  李小建 《世界地理研究》2003,12(2):39-46

本文从分析企业网络的发育和完善程度出发，探讨影响网络创新能力的因素。文章指出，网络发育程度与创新能力(创新数量、创新发生的频率)是正相关的。从宏观上讲网络越密集、各种正式和非正式联系越有效、网络联系越稳定、网络自我更新能力越强、网络的开放性越强、网络越能根植于当地的良好的区域环境，越容易激发创新；从微观上讲，网络中行为主体的学习能力越强，其创新发生频率越高，创新能力越强。  相似文献   

处理DEM中闭合洼地和平坦区域的一种新方法   总被引：14，自引：5，他引：14       下载免费PDF全文

孔凡哲  芮孝芳 《水科学进展》2003,14(3):290-294

数字高程模型(DEM)中的闭合洼地和平坦区域影响着流域排水网络的自动提取.目前已提出很多方法来处理这两种地形,但均针对已经形成的DEM单元网格进行处理,结果往往生成伪河道及平行河道.在回顾分析了这些方法存在的问题后,提出了一种新的处理方法,该法认为DEM中的闭合洼地和平坦区域是由于低质量的资料输入、生成DEM时的内插误差等引起的.通过增加输入地形高程信息,避免了DEM中平坦区域和闭合洼地的生成,从而使由DEM生成的河网与实际河网能够精确拟合.实例分析表明,该方法效果明显.  相似文献   

Multiscale Roughness Analysis of Particles: Application to the Classification of Detrital Sediments     

Hervé Drolon  Bernard Hoyez  Fabrice Druaux  Alain Faure 《Mathematical Geology》2003,35(7):805-817

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人工神经网络与分析测试技术的研究与发展   总被引：8，自引：0，他引：8  

罗立强  马光祖 《岩矿测试》1997,16(4):267-276

回顾了人工神经网络研究的发展历程，简要介绍了神经网络模型与算法，对分析测试技术和相关学科中的人工神经网络研究及在流程控制、错误诊断、参数估计、传感器模型、模式识别与分类、环境监测与治理及光谱与化学分析中的应用等作了评述。引用参考文献１１３篇。  相似文献   

Generating fracture networks using iterated function systems     

U. Mohrlok  R. Liedl 《International Journal of Earth Sciences》1996,85(1):92-95

In order to model flow and transport in fractured rocks it is important to know the geometry of the fracture network. A stochastic approach is commonly used to generate a synthetic fracture network from the statistics measured at a natural fracture network. The approach presented herein is able to incorporate the structures found in a natural fracture network into the synthetic fracture network. These synthetic fracture networks are the images generated by Iterated Function Systems (IFS) as introduced by Barnsley (1988). The conditions these IFS have to fulfil to determine images resembling fracture networks and the effects of their parameters on the images are discussed. It is possible to define the parameters of the IFS in order to generate some properties of a fracture network. The image of an IFS consists of many single points and has to be suitably processed for further use.  相似文献   

人工神经网络在岩体初始应力场反演中的应用   总被引：15，自引：6，他引：15  

易达  徐明毅  陈胜宏  葛修润 《岩土力学》2004,25(6):943-946

岩土工程问题的有限元分析一般需要考虑初始地应力场，而可供工程应用的初始应力值，主要靠少数实测资料。根据少数测点值，采用人工神经网络与有限元相结合的方法求解岩体初始应力场。通过算例说明：文中所提方法是合理的。  相似文献