通渝隧道围岩变形的神经网络预测

隧道新奥法施工中 ,常以围岩变形量作为评判围岩稳定性和支护结构经济合理性的重要指标。公路隧道围岩变形量是随时间而变化的数据序列 ,因而可以建立一些实时跟踪预测模型和方法。根据通渝隧道围岩拱顶下沉位移变形的特性 ,采用神经网络技术来预测其变形量 ,结果表明该方法简易、有效     

美国长期生态研究计划：背景、进展和前景

由美国国家科学基金会支持的长期生态研究计划于1980年启动，至今在理论研究、开发技术和服务社会方面都取得了举世瞩目的成就。该计划的发展分为 3个阶段，每一阶段大约为10年。在其发展的第一个阶段，是以研究站所代表的生态系统为研究对象，主要开展了生态系统的过程与格局方面的研究并系统采集和存贮了有关数据；在1990 -2000年的第二个发展阶段中，其研究工作的重点是开展跨站的网络研究和人类活动对生态系统的影响，以揭示生态系统的过程与格局在较大空间尺度上的特征；按照规划，美国长期生态研究计划的发展进入到第三个阶段后，其工作的重点是开展综合研究、进行生态预测和更好地为社会发展服务，同时加强生物多样性的研究和信息学的发展。     

Research on the effect estimation of seismic safety evaluation

IntroductionItisdefinitelystipulatedintheLawofthePeople'sRepublicofChinaonProtectingagainstandMitigatingEarthquakeDisastersthattheseismicsafetyevaluationmustbemadeformajorprojects(includinglifelineprojects)and,accordingtotheresultsobtained,theseismicresistancerequirementsshouldbedetermined.Thenecessityofseismicsafetyevaluationhasbeenrecog-nizedgradually,butthetopicontheeffectofsafetyevaluationhasnotbeenreferredmuch.Gener-allyspeaking,althoughmostpeopleapprovethesocialeffectofsafetyevaluatio…     

大别山南部宿松磷矿含磷地层的时代归属与变形特征及其构造评价

根据对大别山南部宿松磷矿含磷地层的区域分布、地层序列、时代归属、构造变形的系统研究,提出磷矿层属震旦系的新认识。含磷岩系经受了两次强烈的变形改造,原始层理经过了强烈改造,宿松磷矿构成总体包络面呈北西西走向、向南倾斜的褶皱化单斜。矿层的多层化、尖灭复合和加厚现象等主要受构造的控制,而非完全受古地形的控制。用褶皱的观点对原先勘探剖面中的磷矿体进行了重新圈连,籍以指导磷矿的调查、评价和开采。最后对磷矿分布的古地理特征进行了讨论,并从构造的观点对磷矿进行了评价。     

人工神经网络在岩体质量分级中的应用

结合四川省金沙江某水电站工程实例，应用BP人工神经网络方法建立3层BP网络模型，选取岩石单轴抗压强度等6个影响因素为输入变量，对坝基复杂岩体进行质量分级。通过机算机Visual C 语言编程实现神经网络模型，进行网络的学习和运算。以神经网络合理结构分析方法选取合理结构，确定合理隐层单元的数量，提高网络测试的精度。对测试结果的分析发现，经过优化的BP网络模型经多次学习后，测试精度提高，结果可靠，取得较好的实际应用效果。     

昌马水库右岸山体稳定性研究

昌马水库导流排砂洞塌方导致右岸山体发生松动 ,本文在大量地质资料的基础上 ,对右岸岩体裂隙网络进行模拟 ,同时 ,采用极限分析能量法和有限元数值模拟方法等对右岸山体的稳定性进行分析研究 ,并提出相应的加固方案。     

许昌麦岭水源地可开采量的水均衡法计算

根据许昌麦岭镇多年地下水动态观测资料,利用水均衡法原理,对水源地边界地质条件、补给与排泄的关系进行研究,对地下水允许开采量进行综合评价,提出水源地水量开采的建议。     

Damage Evaluation of Agro-meteorological Hazards in the Maize-Growing Region of Songliao Plain,China: Case Study of Lishu County of Jilin Province

Agro-meteorological hazards such as drought, waterlogging and cool summer occur with very high frequency and affect maize production and social-economic development in the maize-growing region of Songliao Plain, China. Moreover, both the frequency of these hazards and loss from them are considered to be increasing with global warming. The purpose of this paper is to quantitatively analyze the relationships between the fluctuation of maize yield and drought, waterlogging and cool summer, and to evaluate the consequences of these hazards in the maize-growing area of Songliao Plain, taking Lishu county as a case study area based on GIS (Geographic Information System). Crop yield-climate analysis and regression analysis were employed to analyze and quantify relationships between the fluctuation of maize yield and drought, waterlogging and cool summer, and to evaluate the consequences of these hazards. The parameters and model of damage evaluation were presented using weighted comprehensive analysis, and the degree of damage of drought, waterlogging and cool summer to maize production was comprehensively evaluated and regionalized. It is shown that from 1949 to 1990, the negative value years of the fluctuation of maize yield due to meteorological hazards accounted for 55% of seasons, of which 14% was caused by drought, 30% by waterlogging, 4% by cool summer and drought, 9% by cool summer and waterlogging, 13% by drought and waterlogging, 30% by drought, waterlogging and cool summer. Studies on the instability and spatial variation of the fluctuations in maize yield in Lishu county showed that the middle plains are stable areas to climatic influence, while southeastern hills and low mountains, the low lands of the plains along the East Liao River and the western plain are unstable areas in terms of areas in maize yield. The synthetic index of the degree of damage to maize of drought, waterlogging and cool summer showed a strong positive correlation with the ratio of the amount damaged to the normal yield of maize. This suggests that this index can be used to evaluate such damage. The degree of damage of drought, waterlogging and cool summer to maize in Lishu county shows the regional characteristics, which increase gradually from the center to the west and east, this being almost identical with the spatial distribution of the fluctuation of maize yield due to these hazards. This study can be expected to provide the basis for developing strategies to mitigate agro-meteorological hazards and reducing the losses from them, and adjust the medium and long-term distribution of agricultural activities so as to adapt to environmental changes.     

Determination and application of the weights for landslide susceptibility mapping using an artificial neural network

The purpose of this study is the development, application, and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management and manipulation. Landslide locations and landslide-related factors such as slope, curvature, soil texture, soil drainage, effective thickness, wood type, and wood diameter were used for analyzing landslide susceptibility. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence. For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index (LSI) was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.     

London and Frankfurt in Europe's evolving financial centre network

The launch of the Euro and the location of the European Central Bank in Frankfurt initially was seen as a threat to London's pre-eminent position in European financial geographies. This paper explains why in fact this was not the case. To do this, the paper is divided in two. Firstly, it reviews the literatures that help to explain financial geographies. It is argued that we need to move away from investigating attribute properties such as financial turnover and instead examine the role of networks and interdependencies in producing financial geographies. Secondly, it identifies London's dominance and Frankfurt's growth as a complementary centre through quantitative analysis and then explains how European networks and interdependencies produce this, based on insights from interviews with investment bankers and insurance institution workers in the two cities.