Greening as strategic development in industrial change - Why companies participate in eco-networks   总被引：1，自引：0，他引：1  

Eckhard Störmer 《Geoforum》2008,39(1):32-47

Networking between companies and other regional key actors has grown into a widespread instrument for economic development since the 1990s. Participatory networks have formed the concept for many activities of Local Agenda 21. Simultaneously, economic geography has focused on network theories to explain innovation in and the economic success of regions.This article focuses on the reasons why individual actors participate in environmentally oriented information networks. The questions approached are: Does the concept of learning within networks influence a firm’s development? How do the participants interact with each other? What effects do the networks have on their environment (arenas)?The changing arenas of a firm are analysed with regard to environmental concerns. These changes need to be anticipated for reliable strategies. To gain information and knowledge about current behaviour and activities, the functions of networks as learning platforms are discussed. Drawing upon arguments from different network theories, the motivations of participating in a network are threefold: actor and firm oriented, network internal (inter-firm), and network external. From these, a generic target cube of network motivations and actions is set up.The concept is reviewed by examining 12 ‘regional environmental information-oriented corporation networks’ (RUN) in the Greater Munich Area. The empirical material reveals that this type of network does not provide a guarantee for significant improvements in a firm’s environmental behaviour. However, participants learn about best practices while pursuing explicit or implicit aims as to influence their arenas.  相似文献   

DEM analysis of the crack propagation in brittle clays under uniaxial compression tests   总被引：2，自引：0，他引：2  

Luis F. Vesga  Luis E. Vallejo  Sebastian Lobo‐Guerrero 《国际地质力学数值与分析法杂志》2008,32(11):1405-1415

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Numerical estimation of REV and permeability tensor for fractured rock masses by composite element method   总被引：2，自引：0，他引：2  

S.‐H. Chen  X.‐M. Feng  S. Isam 《国际地质力学数值与分析法杂志》2008,32(12):1459-1477

The Monte Carlo method is used to generate parent stochastic discrete fracture network, from which a series of fractured rock samples of different sizes and orientations are extracted. The fracture network combined with a regular grid forms composite element mesh of the fractured rock sample, in which each composite element is composed of sub‐elements incised by fracture segments. The composite element method (CEM) for the seepage is implemented to obtain the nodal hydraulic potential as well as the seepage flow rates through the fractured rock samples. The application of CEM enables a large quantity of stochastic tests for the fractured rock samples because the pre‐process is facilitated greatly. By changing the sizes and orientations of the samples, the analysis of the seepage characteristics is realized to evaluate the variation of the permeability components, the existence of the permeability tensor and the representative element volume. The feasibility and effectiveness are illustrated in a numerical example. Copyright © 2008 John Wiley & Sons, Ltd.  相似文献   

喜马拉雅山脉的地质地貌特征:来自SRTM数字高程模型和降水量数据的约束   总被引：3，自引：1，他引：2       下载免费PDF全文

王猛  刘焰  何延波  魏东 《地质科学》2008,43(3):603-622

利用GTOPO30和SRTM3数字高程(DEM)数据,提取了喜马拉雅山脉(造山带)的数字高程模型并对其进行了地质地貌的初步分析。从SRTM3数字高程数据提取出坡度数据,初步分析了喜马拉雅山脉坡度和高程的特征。数字高程和坡度图清楚地展现了喜马拉雅大型断裂带(构造边界)的空间分布特征。分析了中国气象局下属的西藏、青海、四川和云南4省区气象观测台站55年来的年平均降水量观测数据、喜马拉雅山脉南坡的年平均降水量数据、喜马拉雅DEM和裂变径迹数据,发现喜马拉雅山脉从东至西,年平均降水量逐渐减少,地形起伏逐渐变小,而高程渐次升高,与此同时剥蚀速率降低;从北至南,年平均降水量逐渐增加,地形起伏增大,高程快速降低,而剥蚀速率则急剧升高。这充分说明了喜马拉雅年平均降水量大的地区,地表剥蚀作用相对较强,年平均降水量小的地区,地表剥蚀作用则较弱,即:在喜马拉雅地区,长周期的地表剥蚀过程(可长达数个百万年时间尺度)和短周期(仅仅50年)的降水量观测是耦合的。  相似文献   

Implementation of reconstructed geomorphologic units in landslide susceptibility mapping: the Melen Gorge (NW Turkey)   总被引：6，自引：2，他引：4  

T. Gorum  B. Gonencgil  C. Gokceoglu  H. A. Nefeslioglu 《Natural Hazards》2008,46(3):323-351

In the international literature, although considerable amount of publications on the landslide susceptibility mapping exist, geomorphology as a conditioning factor is still used in limited number of studies. Considering this factor, the purpose of this article paper is to implement the geomorphologic parameters derived by reconstructed topography in landslide susceptibility mapping. According to the method employed in this study, terrain is generalized by the contours passed through the convex slopes of the valleys that were formed by fluvial erosion. Therefore, slope conditions before landsliding can be obtained. The reconstructed morphometric and geomorphologic units are taken into account as a conditioning parameter when assessing landslide susceptibility. Two different data, one of which is obtained from the reconstructed DEM, have been employed to produce two landslide susceptibility maps. The binary logistic regression is used to develop landslide susceptibility maps for the Melen Gorge in the Northwestern part of Turkey. Due to the high correct classification percentages and spatial effectiveness of the maps, the landslide susceptibility map comprised the reconstructed morphometric parameters exhibits a better performance than the other. Five different datasets are selected randomly to apply proper sampling strategy for training. As a consequence of the analyses, the most proper outcomes are obtained from the dataset of the reconstructed topographical parameters and geomorphologic units, and lithological variables that are implemented together. Correct classification percentage and root mean square error (RMSE) values of the validation dataset are calculated as 86.28% and 0.35, respectively. Prediction capacity of the different datasets reveal that the landslide susceptibility map obtained from the reconstructed parameters has a higher prediction capacity than the other. Moreover, the landslide susceptibility map obtained from the reconstructed parameters produces logical results.  相似文献   

流域水文模型参数识别的现代优化方法研究进展   总被引：1，自引：1，他引：0  

武震  张世强  张小文 《冰川冻土》2008,30(1):64-71

水文参数优化是水文模型发展中的一个重要部分,针对水循环过程模拟中的流域水文模型参数识别的复杂优化问题,回顾了水文模型优化算法的发展历程,对国内外水文模型参数识别算法的最新进展进行了阐述.介绍了模拟退火算法、遗传算法、SCE-UA、粒子群算法等常用算法的参数设定及一般流程,并对编码遗传算法、单纯形混合加速遗传算法和运用融合技术的几种遗传算法以及其它几种常用算法在新安江模型中的优化结果进行了比较,认为混合加速遗传算法是一种较好的方法.在系统研究现代优化算法与传统优化算法的基础上,建立各种优化算法的融合技术和法则可能是进一步提高参数优化算法性能的方向.  相似文献   

水库库岸滑坡涌浪的传播与爬高研究   总被引：5，自引：0，他引：5  

汪洋  殷坤龙 《岩土力学》2008,29(4):1031-1034

基于流体力学明渠非恒定流的连续性方程、运动方程和沿程水头损失理论,把滑坡涌浪衰减过程分为急剧衰减和缓慢衰减两个阶段来考虑,并认为急剧衰减阶段的涌浪的衰减符合指数衰减规律,缓慢衰减阶段符合明槽水流的沿程水头损失规律,结合初始涌浪高度对涌浪沿岸的传播高度及爬坡高度进行了计算。以新滩滑坡为例对涌浪的传播及爬坡高度进行了计算,得出了滑坡涌浪衰减先快后慢以及传播3 km时的涌浪高度只有初始涌浪高度的30 %以及传播10 km时涌浪高度只有初始涌浪高度的13 %的规律。  相似文献   

陕西白河县月儿潭绿松石与次生磷钙铝矾研究     

石振荣  蔡克勤 《岩石矿物学杂志》2008,27(2):164-170

对陕西省白河县月儿潭风化严重的绿松石样品进行了岩石薄片观察、化学成分测试、X射线粉晶衍射和红外吸收光谱分析等研究.结果表明,绿松石风化分解由天蓝色退色成黄绿色,最后变成白色,结构也由致密细腻变得松散多孔,主要原因是发生了硫酸根对磷酸根的交代作用,最终的交代产物主要是磷钙铝矾.  相似文献   

Re-Os同位素对峨眉山大火成岩省成因制约的探讨   总被引：6，自引：3，他引：3  

史仁灯  郝艳丽  黄启帅 《岩石学报》2008,24(11):2515-2523

峨眉山大火成岩省（ELIP）主要由玄武岩、玄武质火山碎屑岩及少量的苦橄岩（包括越南的科马提岩）、长英质岩石以及层状岩体和岩墙组成,其物质来源直接关系到其成因是否与地幔柱活动有关。Re-Os同位素体系是地核、地幔和地壳物质的最佳示踪剂。前人对ELIP内的Re-Os同位素研究表明,低Ti玄武岩的Os含量为0．006×10^-9-0．40010^-9,^187Os／^188Os初始值为0．1371～1．403,并提出其与地幔柱活动有关;而高Ti玄武岩的Os含量为0．00410^-9～0．56010^-9,^187Os／^188Os初始值为0．1271～5．19,认为起源于大陆岩石圈地幔或地幔柱上升过程中受到大量岩石圈地幔“混染”（xu JF et al．,2007）;科马提岩的0s含量为1．2410^-9～7．0010^-9,^187Os／^188Os初始值为0．1251～0．1261,苦橄岩的Os含量为0．3210^-9～2．32910^-9,^187Os／^188Os初始值为0．1233～0．1266,指示苦橄岩和科马提岩均来自亏损地幔源区（Hanski et al．,2004;陈雷等,2007）。本文利用Os含量最低、^187Os／^188Os最高的高Ti玄武岩作为地壳端员,用铁质陨石、原始上地幔（PUM）和亏损地幔（DMM）作为地核和各种地幔端员,分别做二元混合计算,结果显示绝大多数玄武岩和所有苦橄岩及科马提岩均落在地壳和DMM混合曲线附近,并且邻区特提斯洋地幔岩与DMM具有相近的Os含量和^187Os／^188Os组成,据此推测峨眉山火成岩的形成与特提斯洋的活动有关,主要受控于地壳和亏损地幔的相互作用。  相似文献   

基于AGA的SVM需水预测模型研究   总被引：1，自引：0，他引：1  

张灵  陈晓宏  刘丙军  王兆礼 《水文》2008,28(1):38-42,46

需水预测是一个由城市人口、工业水平、社会经济水平共同作用的多因素、多层次的复杂非线性系统.其结果将直接影响受区域水资源承载力约束的产业结构、布局形态等决策.作为一种集中参数预报方法,支持向量机方法具有对未来样本的较好的泛化性能,对于这类资料缺乏、系统结构尚欠清晰的问题可以取得较好的模拟和预测结果.基于此,本文将支持向量机方法引入需水预测领域,建立了需水预测支持向量机模型.同时,本文将加速遗传算法和支持向量机方法耦合起来,构造了支持向量机模型参数的自适应优化算法.模型在珠海市的应用实例表明:与简单遗传算法比较,AGA的模型参数寻优效率更高;与BP神经网络模型相比,SVM模型较好地解决了小样本、经验性等问题,并取得了较高的预测精度.  相似文献