Extreme Rainfall Events and Associated Natural Hazards in Alaknanda Valley, Indian Himalayan Region   总被引：2，自引：0，他引：2  

JOSHI Varun KUMAR Kireet 《山地科学学报》2006,3(3):228-236

Introduction The Himalaya is considered to be the youngest mountains on the earth, and is tectonically very active, and hence inherently (geologically) vulnerable to hazards. Extreme rainfall events, landslides, debris flows, torrents and flash floods due…  相似文献   

Spatial Variability of Rock Depth in Bangalore Using Geostatistical, Neural Network and Support Vector Machine Models     

T. G. Sitharam  Pijush Samui  P. Anbazhagan 《Geotechnical and Geological Engineering》2008,26(5):503-517

Geospatial technology is increasing in demand for many applications in geosciences. Spatial variability of the bed/hard rock is vital for many applications in geotechnical and earthquake engineering problems such as design of deep foundations, site amplification, ground response studies, liquefaction, microzonation etc. In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 km². In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, Geostatistical model based on Ordinary Kriging technique, Artificial Neural Network (ANN) and Support Vector Machine (SVM) models have been developed. In Ordinary Kriging, the knowledge of the semi-variogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of the Bangalore, where field measurements are not available. A new type of cross-validation analysis developed proves the robustness of the Ordinary Kriging model. ANN model based on multi layer perceptrons (MLPs) that are trained with Levenberg–Marquardt backpropagation algorithm has been adopted to train the model with 90% of the data available. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing loss function has been used to predict the reduced level of rock from a large set of data. In this study, a comparative study of three numerical models to predict reduced level of rock has been presented and discussed.  相似文献   

Dynamic properties of green water event in the overtopping of extreme waves on a fixed dock     

Nobuhito Mori  Daniel T. Cox 《Ocean Engineering》2003,30(16):2021-2052

A statistical model is developed to predict wave overtopping volume and rate of extreme waves on a fixed deck. The probability density function for the volume and rate of overtopping water are formulated based on the truncated Weibull distribution with the assumption of local sinusoidal profile for small amplitude waves. Sensitivity to the wave nonlinearity parameter and deck clearance is discussed. The statistical model is compared to laboratory data of the instantaneous free surface elevation measured in front of a fixed deck, and overtopping volume and overtopping rate measured at the leading edge of the deck. The statistical theory compared well with the measured exceedance probability seaward of the deck. The model prediction of the exceedance probability of deck overtopping gave qualitatively good agreement for large overtopping values.  相似文献   

Evaluation of long-term extreme response statistics of jack-up platforms   总被引：1，自引：0，他引：1  

M. J. Cassidy  P. H. Taylor  R. Eatock Taylor  G. T. Houlsby 《Ocean Engineering》2002,29(13):1603-1631

This paper is concerned with the models appropriate for the dynamic assessment of jack-ups, concentrating particularly on the long-term response due to random ocean waves and on work-hardening plasticity models used for spud-can response. A methodology for scaling of short-term statistics, calculated using a Constrained NewWave technique, is shown in a numerical experiment for an example jack-up and central North Sea location. The difference in long-term extreme response statistics due to various footing assumptions is emphasised. Results for two environmental load conditions are described (one excluding and one including wind and current effects) and the role of sea-state severity in the variation of short-term extreme response statistics is also highlighted.  相似文献   

On the parametric resonance of container ships     

Metin Taylan   《Ocean Engineering》2007,34(7):1021-1027

This work deals with parametric resonance which poses a great danger especially for container ships sailing in following or head seas. Important parameters that are effective in roll resonance are pointed out. For this purpose, a containership is taken as an example to analyze its stability in longitudinal waves based on the method worked out by American Bureau of Shipping (ABS). Unfavorable sailing conditions such as heading and speed, which directly depend on the environmental conditions, have been determined for this particular ship. These conditions may be reported to the master to guide him to keep his ship out of parametric resonance zones. Numerical details of the procedure have been worked out and provided as well.  相似文献   

便携式电子地图设计中需解决的几个问题     

胡武强  杨华 《北京测绘》2008,(4)

软性显示器和投影技术超微型化的发展,使得电子地图有足够的空间满足便携式电子地图的设计需求,本文通过介绍几种便携式材质的特性,提出便携式电子地图设计中需解决的几个硬件技术问题。  相似文献   

基于支持向量机的CBERS-02卫星影像信息提取   总被引：1，自引：0，他引：1  

温兴平  胡光道  杨晓峰 《测绘科学》2008,33(5)

CBERS卫星是由中国空间技术研究院与巴西空间研究院联合研制的地球资源遥感卫星,CBERS-02卫星数据总体质量比CBERS-01卫星有所提高,本文利用支持向量机方法对CBERS-02卫星影像信息进行提取。研究中首先用6S模式对影像进行大气校正,然后选择RBF为支持向量机方法的核函数,并用交叉验证方法得到影响RBF核函数的两个最佳参数值进行学习完成信息提取,最后将提取结果制作成矢量图。通过研究得出用大气校正后的数据进行信息提取分类精度有所提高;与最大似然法和最小距离法相比,支持向量机方法分类精度较高。通过将研究结果与ETM+影像进行比较得出,CBERS-02卫星影像精度能够满足应用需求并能代替TM/ETM+数据开展研究工作。  相似文献   

Automated Kerogen Classification in Microscope Images of Dispersed Kerogen Preparation     

L. I. Kuncheva  J. J. Charles  N. Miles  A. Collins  B. Wells  I. S. Lim 《Mathematical Geosciences》2008,40(6):639-652

We develop the classification part of a system that analyses transmitted light microscope images of dispersed kerogen preparation. The system automatically extracts kerogen pieces from the image and labels each piece as either inertinite or vitrinite. The image pre-processing analysis consists of background removal, identification of kerogen material, object segmentation, object extraction (individual images of pieces of kerogen) and feature calculation for each object. An expert palynologist was asked to label the objects into categories inertinite and vitrinite, which provided the ground truth for the classification experiment. Ten state-of-the-art classifiers and classifier ensembles were compared: Naïve Bayes, decision tree, nearest neighbour, the logistic classifier, multilayered perceptron (MLP), support vector machines (SVM), AdaBoost, Bagging, LogitBoost and Random Forest. The logistic classifier was singled out as the most accurate classifier, with an accuracy greater than 90. Using a 10 times 10-fold cross-validation provided within the Weka software, we found that the logistic classifier was significantly better than five classifiers (p<0.05) and indistinguishable from the other four classifiers. The initial set of 32 features was subsequently reduced to 6 features without compromising the classification accuracy. A further evaluation of the system alerted us to the possible sensitivity of the classification to the ground truth that might vary from one human expert to another. The analysis also revealed that the logistic classifier made most of the correct classifications with a high certainty.  相似文献   

Learning to trade ethically: Knowledgeable capitalism, retailers and contested commodity chains     

Alex Hughes   《Geoforum》2006,37(6):1008-1020

This paper explores what happens when corporations engage explicitly in practices of organisational learning not only to become better capitalists by generating ever more innovative ways of maintaining profitability, improving competitiveness and maximising shareholder value, but also to become more responsible corporate citizens in their business practices. In particular, I evaluate the ways in which UK food and clothing retailers are learning to develop their ethical trading programmes in response to political calls for more responsible trading. Thrift’s [Thrift, N., 2005. Knowing Capitalism. Sage, London] notion of ‘knowledgeable, or soft, capitalism’ is adopted to understand the creative and experimental ways in which retailers and their mentors (ethical consultancies, social auditors and multi-stakeholder organisations) are learning to trade ethically. Two specific examples of formal learning spaces experienced by UK food and clothing retailers are examined: (i) training courses on social auditing and (ii) corporate awareness-raising courses on ethical trade. These courses are shown to encompass various participative and affective practices of learning. And while particular limits to the success of these courses are argued to exist, ethical learning practices discussed in this paper are nonetheless suggested to play a role in the making of new, albeit moderate, forms of responsible capitalism.  相似文献   

Patterns in the Turkish reinsurance claim data, 1998–2002: An application of the extreme value theory     

B. Burçak Başbuğ  Henry P. Wynn 《Natural Hazards》2006,39(2):329-342

The devastating 1999 Marmara and Düzce earthquakes led to a significant increase in the earthquake studies in Turkey in geological, engineering and financial aspects. Extreme Value Theory (EVT) has a range of applications from stock market changes to natural disasters like floods and hurricanes. Here EVT is fitted to the ordinary and earthquake reinsurance claims of Turkey.  相似文献