Climate change perceptions and their individual-level determinants: A cross-European analysis     

《Global Environmental Change》2019

There is now an extensive literature on the question of how individual-level factors affect climate change perceptions, showing that socio-political variables, notably values, worldviews and political orientation, are key factors alongside demographic variables. Yet little is known about cross-national differences in these effects, as most studies have been conducted in a single or small number of countries and cross-study comparisons are difficult due to different conceptualisations of key climate change dimensions. Using data from the European Social Survey Round 8 (n = 44,387), we examine how key socio-political and demographic factors are associated with climate change perception across 22 European countries and Israel. We show that human values and political orientation are important predictors of climate change beliefs and concern, as are the demographics of gender, age, and education. Certain associations with climate change perceptions, such as the ones for the self-transcendence versus self-enhancement value dimension, political orientation, and education, are more consistent across countries than for gender and age. However, even if the direction of the associations are to a large extent consistent, the sizes of the effects are not. We demonstrate that the sizes of the effects are generally smaller in Central and Eastern European countries, and that some demographic effects are larger in Northern European as compared to Western European countries. This suggests that findings from one country do not always generalize to other national contexts.  相似文献   

Measuring,mapping and quantifying the effects of trust and informal communication on transboundary collaboration in the Great Lakes fisheries policy network     

《Global Environmental Change》2019

Ecosystem-based management of fisheries and other transboundary natural resources require a number of organizations across jurisdictions to exchange knowledge, coordinate policy goals and engage in collaborative activities. Trust, as part of social capital, is considered a key mechanism facilitating the coordination of such inter-organizational policy networks. However, our understanding of multi-dimensional trust as a theoretical construct and an operational variable in environmental and natural resource management has remained largely untested. This paper presents an empirical assessment of trust and communication measures applied to the North American Great Lakes fisheries policy network. Using a scale-based method developed for this purpose, we quantify the prevalence of different dimensions of trust and in/formal communication in the network and their differentiated impacts on decision-making and goal consensus. Our analysis reveals that calculation-based ‘rational trust’ is important for aligning mutual goals, but relationship-based ‘affinitive trust’ is most significant for influencing decision-making. Informal communication was also found to be a strong predictor of how effectively formal communication will influence decision-making, confirming the “priming” role of informal interactions in formal inter-agency dealings. The results also show the buffering and interactive functions of these components in strengthening institutional resilience, with procedural trust undergirding the system to compensate for a lack of well-developed relationships. Overall, this study provides evidence to suggest that informal communication and multi-dimensional trust constitute a crucial element for improving collaboration and reducing conflict in the networked governance of transboundary natural resource systems.  相似文献   

基于小波长短期记忆网络的风电功率超短期概率预测     

王朋  孙永辉  翟苏巍  候栋宸  王森 《南京气象学院学报》2019,11(4):460-466

随着大规模的风电并网,风电所具有的间歇性与随机性对电力系统的稳定性产生了很大的影响,风电功率预测成为当前解决该问题重要的方式之一.本文利用长短期记忆（LSTM）网络良好的时序记忆特性,将小波分解技术与LSTM深度网络结合,提出基于小波长短期记忆网络的风电功率超短期概率预测模型.首先通过小波分解技术将原始时间序列进行平稳化处理,再建立各子序列样本的LSTM网络预测模型,借助最大似然估计法估计预测误差的高斯分布函数,最终实现对未来4 h时刻的风电功率概率区间预测.最后,采用中国东北某风电场数据对所提方法进行算例分析,结果表明,将小波分解与深度学习方法结合可以较好地提高预测的精度,提高概率预测的区间可靠性.  相似文献   

循环神经网络在雷达临近预报中的应用          下载免费PDF全文

韩丰  龙明盛  李月安  薛峰  王建民 《应用气象学报》2019,30(1):61-69

该文将循环神经网络（recurrent neural network,RNN）应用于雷达临近预报。使用预测循环神经网络（predictive RNN）架构,利用雷达历史组合反射率因子建模,给出雷达组合反射率因子未来1 h的预报结果。预测循环神经网络的核心是在长短时记忆单元（long short-term memory,LSTM）中增加时空记忆模块,能够提取雷达回波不同尺度的空间特征,配合循环神经网络架构,可以有效解决反射率因子预测问题。北京大兴雷达和广州雷达长时间序列的独立检验结果和2个强对流天气个例检验结果表明:该方法和传统的基于交叉相关法的1 h雷达外推临近预报相比,在20 dBZ和30 dBZ检验项目内,临界成功指数（CSI）可以提升0.15~0.30,命中率（POD）提高0.15~0.25,虚警率（FAR）降低0.15~0.20,该方法对反射率因子强度变化有一定预报能力。  相似文献   

Numerical Modeling of Natural Fracture Distributions in Shale     

LI Yaping  CHEN Xiaowei  SHAO Yongbo 《《地质学报》英文版》2023,97(3):828-840

The production efficiency of shale gas is affected by the interaction between hydraulic and natural fractures. This study presents a simulation of natural fractures in shale reservoirs, based on a discrete fracture network (DFN) method for hydraulic fracturing engineering. Fracture properties of the model are calculated from core fracture data, according to statistical mathematical analysis. The calculation results make full use of the quantitative information of core fracture orientation, density, opening and length, which constitute the direct and extensive data of mining engineering. The reliability and applicability of the model are analyzed with regard to model size and density, a calculation method for dominant size and density being proposed. Then, finite element analysis is applied to a hydraulic fracturing numerical simulation of a shale fractured reservoir in southeastern Chongqing. The hydraulic pressure distribution, fracture propagation, acoustic emission information and in situ stress changes during fracturing are analyzed. The results show the application of fracture statistics in fracture modeling and the influence of fracture distribution on hydraulic fracturing engineering. The present analysis may provide a reference for shale gas exploitation.  相似文献   

基于卷积神经网络的磁异常反演     

薛瑞洁  熊杰  张月  王蓉 《现代地质》2023,37(1):173-183

针对传统反演方法存在的初始模型依赖、计算时间较长等问题,提出一种基于卷积神经网络的磁异常反演方法。该方法首先设计大量磁异常体模型,进行正演模拟产生样本数据集;接着借鉴经典的卷积神经网络VGG-13设计了一种全新的VGG磁异常反演网络(VGGINV);然后使用样本数据集训练该网络,并优化网络参数;最后对理论模型和实测数据进行反演实验。实验结果表明,该方法可以准确地反演出磁异常体的位置和磁化强度,具有较强的学习能力和一定的泛化能力,能有效解决磁异常数据反演问题。  相似文献   

砂样图像岩屑自动分割提取方法          下载免费PDF全文

夏文鹤  唐印东  李皋  韩玉娇  林永学  吴雄军  石祥超 《岩石矿物学杂志》2023,42(6):894-906

通过将砂样图像进行单颗粒分割,识别砂样成分,可显著提高砂样岩性分析的准确性和效率。现有的砂样图像分割方法主要以传统分水岭算法和卷积神经网络为主,但由于对单颗粒岩屑轮廓细节提取不足,误分割率高。本文提出一种以图像融合算法为桥梁,将卷积神经网络和分水岭算法相结合的单颗粒图像分割提取方法。首先利用改进的Mask R-CNN网络快速分割砂样原图,获得其初分割图像;然后,将初分割图像与砂样原图进行融合,再使用改进的分水岭算法对融合结果进行分割;最后,利用砂样原图坐标点匹配方法,将分水岭分割得到的结果图像进行修正,完成单颗粒岩屑图像提取。实验结果表明,本文的单颗粒自动分割提取方法准确率高达96.77%,且模型更轻量和精准,为岩屑图像分割提供了一种可行且有效的方法,可满足有效测算油藏层构造变化、查找潜在沉积物源及储层动态变化的需求。  相似文献   

全球锑原材料贸易格局演化分析     

王春辉  王安建  孙旭 《地球学报》2023,44(2):378-386

随着中国锑矿产量下降以及全球新能源领域对锑需求量的增加, 全球锑原材料供需格局正在改变。对全球锑原材料贸易格局的现状及演化过程开展分析, 有助于世界各国构建弹性的锑原材料供应链。本文基于物质流与复杂网络分析方法, 定量刻画了四类锑原材料(锑矿石、锑金属、锑初级加工品、再生锑)的全球贸易格局(2002—2020年), 分析了典型国家(地区)的锑原材料贸易结构及贸易地位变化特征, 总结了贸易格局的演化规律。研究发现: (1)锑初级加工品是全球最主要的贸易品种, 其贸易量占全球锑原材料总贸易量的一半以上; (2)中国和美国分别是贸易地位排名前两位的国家, 印度、欧盟、韩国是贸易地位上升最快三个国家(地区); (3)欧盟锑金属的进口来源呈现明显的多元化趋势, 显著降低了对中国的进口依赖, 表明欧盟近些年实施的关键原材料多元化进口战略取得了显著成效; (4)中国在全球锑原材料供应格局中的绝对优势地位在下降, 与此同时, 全球锑原材料贸易格局正朝着更加多元的方向发展。  相似文献   

萤石典型产品国际贸易竞争格局演变     

陈韵冰  王星星  周凤英 《地球学报》2023,44(2):395-403

萤石作为一种重要的非金属战略性矿产资源,受到各国(地区)的高度重视。由于全球萤石资源储量有限、分布不均,萤石产品的供需矛盾不断增强,激化了萤石资源进出口之间的竞争。本文主要研究了萤石资源国际贸易,以无机氟化工产业链为切入点,选取酸级萤石、电子级氢氟酸、六氟磷酸锂为研究对象,运用复杂网络方法,构建了2000—2020年全球萤石产品进口竞争网络,分析其格局、演变特征,国家(地区)间竞争特点以及中国萤石产品的竞争状况。结果发现:全球萤石产品之间的竞争越来越激烈,各阶段的累积度分布都遵循幂律分布。竞争强度占比前20%的国家(地区)显示出更直观的集中化趋势。近20年来美国一直是酸级萤石进口竞争的矛盾中心。电子级氢氟酸和六氟磷酸锂的进口竞争网络的核心国家(地区)是不断演变的。建议中国等萤石资源储量丰富的国家(地区),合理规划萤石产业,优化萤石资源供需格局、促进萤石产业健康可持续发展。  相似文献   

基于波动理论的结构损伤识别研究进展          下载免费PDF全文

戴东利  杨汉青  杨翔  何伟 《地震工程学报》2022,44(5):1001-1008

目前人们对于结构的使用安全越来越重视,结构在日常使用或灾后的损伤识别检测也变得尤为重要。近年来国内外对于波在结构中的传播理论进行了深入研究,基于波动理论的结构损伤识别方法也取得了一定进展。文章首先介绍波在介质中的传播以及在各种类型结构中的传播规律和传播特性,其次从基于波传播理论的结构损伤识别、基于Lamb波的结构损伤识别、波动理论和神经网络相结合、波动理论与其他技术或算法的融合4个方面对国内外基于波动理论对结构损伤识别方法的研究成果进行综述。  相似文献