应用SVM方法进行沉积微相识别   总被引：15，自引：1，他引：14  

阎辉  张学工  李衍达 《物探化探计算技术》2000,22(2):158-164

作者针对目前沉积微相中的特征提取问题,提出了应用ＳＶＭ（支持向量机）方法进行沉积微相识别的方案。该方法不是象传统方法那样首先试图将原输入空间降维（即特征选择变换）,而是设法将输入空间升维,以求在高维空间中问题变得线性可分（或接近线性可分）。因为升维后只是改变了内积运算,并没有使算法复杂性随着维数的增加而增加,因此这种方法才是可行的。所以。利用该方法更能胜任实际情况。实际处理表明该方法在小样本情况下  相似文献   

联合DBSCAN聚类采样和SVM分类的滑坡易发性评价     

鲍帅  刘纪平  王亮 《震灾防御技术》2021,16(4):625-636

针对基于机器学习的滑坡易发性评价中非滑坡样本选取不规范导致的分类精度较低问题,本文提出联合基于密度的噪声应用空间聚类(Density-Based Spatial Clustering of Applications with Noise,DBSCAN)采样策略和支持向量机(Support Vector Machine,...  相似文献   

基于ELM的风电场短期风速订正技术研究     

张颖超  肖寅  邓华 《气象》2016,42(4):466-471

风速预测是风电场风功率预测的基础,其准确度严重影响着风电场的运行效率。为了提高短期风速预测的准确性,本研究采用了WRF中尺度数值模式,对我国东部沿海某风电场的风速进行预报。在此基础上,利用极限学习机算法(ELM)对WRF模式预报的风速进一步订正。实验结果表明,WRF模式对风速、风向等气象要素有着较好的回报效果,利用ELM算法对WRF模式预报风速进行订正后,预报风速的误差进一步减小,相对均方根误差和相对平均绝对误差降低了20%～30%。与其他的智能算法(BP神经网络、SVM算法)对比分析后得出,ELM算法对WRF模式预报风速具有较好的订正效果,能够有效提高风速预报准确率。  相似文献   

The double-edged sword of learning from disasters: Mortality in the Tohoku tsunami     

《Global Environmental Change》2017

Learning from natural disasters is predominantly regarded as beneficial: Individuals and governments learn to cope and thereby reduce damage and loss of life in future disasters. We argue against this standard narrative and point to two principal ways in which learning from past disasters can have detrimental consequences: First, investment in protective infrastructures may not only stimulate settlement in hazard-prone areas but also foster a false impression of security, which can prevent individuals from fleeing to safe places when hazard strikes. Second, if disaster events in the past did not have catastrophic consequences, affected individuals do not take future events sufficiently seriously. As a consequence, learning from disasters is a double-edged sword that can prevent large scale damage and human loss most of the time but results in the worst case scenario when a disaster occurs at an unexpected scale and public preparedness measures fail. We demonstrate the devastating impact of misplaced trust in public preparedness measures and misleading lessons drawn from past experience for the case of the 2011 Tohoku tsunami. Our paper contributes to the literatures on ‘negative learning’ and ‘hazard maladaptation’ by demonstrating that a lack of past experience with tsunami mortality in a municipality substantively increases mortality in the Tohoku tsunami.  相似文献   

‘A very human business’—Transnational networking initiatives and domestic climate action     

《Global Environmental Change》2019

The past two decades have witnessed a proliferation of transnational networking initiatives aimed at addressing climate change. Previous work has suggested that these initiatives largely achieve their governance functions by fostering learning and resource acquisition. Our particular contribution seeks to advance current understanding of networking initiatives by suggesting that they may additionally perform social and emotional roles which galvanise, energise and motivate actors to pursue actions which advance domestic climate goals. To illustrate our argument, we examine GLOBE International, an inter-parliamentary institution focused on supporting the development of domestic legislation around sustainable development. Based on semi-structured interviews with legislators, we provide evidence that GLOBE functions as a network for learning, and particularly political learning. Yet participation in the group setting of the initiative’s summits has additionally given rise to feelings of unity, emotional energy and inspiration. We conclude by discussing the implications of our findings, which paint a richer, more complex picture of transnational climate governance than previously acknowledged in the literature.  相似文献   

Building Environmental Literacy through Participation in GIS and Multimedia Assisted Field Research     

《The Journal of geography》2012,111(1):10-19

Abstract

A Learning Support System (LSS) that emphasizes experiential research in natural environments using the cutting-edge technologies of GIS and multimedia has been developed for teaching environmental literacy to undergraduate students at the University of Georgia. Computers are used as cognitive tools to create a context in which students become interns in an ecological research center. Students are instructed to conduct research in the form of two field laboratories (the stream and forest laboratories). They accomplish their tasks by collecting data in the field (the State Botanical Garden of Georgia near the campus). They enter the data in the Learning Support System (LSS), and are guided to formulate hypotheses relating to stream water quality and human impact on forest succession for testing. Students also interact with the Environmental Research Support Site (ERSS) within the LSS for explanations to their findings. A specially customized Arc View GIS program within the LSS provides a tool to students for spatial analysis in the case of the forest laboratory. Students and faculty evaluations as well as final examination results confirmed the receptiveness of students to the LSS approach and its effectiveness in the learning of environmental literacy.  相似文献   

Learning effects of interactive decision-making processes for climate change adaptation     

《Global Environmental Change》2014

Learning is gaining attention in relation to governance processes for contemporary environmental challenges; however, scholarship at the nexus of learning and environmental governance lacks clarity and understanding about how to define and measure learning, and the linkages between learning, social interactions, and environment. In response, this study aimed to advance and operationalize a typology of learning in an environmental governance context, and examined if a participatory decision-making process (adaptive co-management) for climate change adaptation fostered learning. Three types of learning were identified: cognitive learning, related to the acquisition of new or the structuring of existing knowledge; normative learning, which concerns a shift in viewpoints, values or paradigms, and relational learning, referring to an improved understanding of others’ mindsets, enhanced trust and ability to cooperate. A robust mixed methods approach with a focus on quantitative measures including concept map analysis, social network analysis, and self-reflective questions, was designed to gauge indicators for each learning type. A participatory decision-making process for climate change adaptation was initiated with stakeholders in the Niagara region, Canada. A pseudo-control group was used to minimize external contextual influences on results. Clear empirical evidence of cognitive and relational learning was gained; however, the results from normative learning measures were inconclusive. The learning typology and measurement method operationalized in this research advances previous treatments of learning in relation to participatory decision-making processes, and supports adaptive co-management as a governance strategy that fosters learning and adaptive capacity.  相似文献   

The political economy of technology support: Making decisions about carbon capture and storage and low carbon energy technologies   总被引：1，自引：0，他引：1  

Asbjørn Torvanger  James Meadowcroft 《Global Environmental Change》2011,21(2):303-312

This article reviews the political economy of government choice around technology support for the development and deployment of low carbon emission energy technologies, such as Carbon Capture and Storage (CCS). It is concerned with how governments should allocate limited economic resources across abatement alternatives. In particular, it explores two inter-related questions. First, should government support focus on a narrow range of options or be distributed across many potential alternatives? Second, what criteria should be considered when determining which specific technologies to support? It presents a simple economic model with experience curves for CCS and renewable energy technologies to explore the lowest cost alternatives for meeting an emission abatement objective. It then explores a variety of economic and political factors that must be considered when governments make decisions about technology support.  相似文献   

Projects,people, professions: Trajectories of learning through a mega-event (the London 2012 case)     

《Geoforum》2015

Planning and organization of large-scale events such as Olympic Games are accomplished by several specialized project organizations, in charge of securing finances, completing the infrastructures, negotiating with multiple stake-holders and the day-to-day management of the actual event. These organizations have to cope with a key challenge. Due to their inherently temporary nature they cannot provide the specialized knowledge and specific “project capabilities” (Davies and Brady) on their own, but have to mobilize them from the past and from outside their boundaries, e.g. from previous events or other mega-projects in the host city. Rather than in permanent organizations, then, the knowledge on preparing and performing mega-events is primarily sedimented and embodied in professionals.Drawing on the planning and organization of the London Olympics 2012 as empirical case, the paper addresses, on the one hand, this particular mobilization process. On the other, it looks at how this process is intertwined with three different trajectories that both affect and are affected by the mega-event: the trajectory of the project that aims to recruit necessary skills; the trajectory of individual persons who perceive working for the Olympics as a rewarding episode in their careers; the trajectory of professional communities that expect learning benefits for the construction and project management industry in the UK.  相似文献   

Learning and climate change     

Brian C. O'Neill  Paul Crutzen  Arnulf Grübler  Minh Ha Duong  Klaus Keller  Charles Kolstad 《Climate Policy》2013,13(5):585-589

Abstract

Learning—i.e. the acquisition of new information that leads to changes in our assessment of uncertainty—plays a prominent role in the international climate policy debate. For example, the view that we should postpone actions until we know more continues to be influential. The latest work on learning and climate change includes new theoretical models, better informed simulations of how learning affects the optimal timing of emissions reductions, analyses of how new information could affect the prospects for reaching and maintaining political agreements and for adapting to climate change, and explorations of how learning could lead us astray rather than closer to the truth. Despite the diversity of this new work, a clear consensus on a central point is that the prospect of learning does not support the postponement of emissions reductions today.  相似文献