The social and political complexities of learning in carbon capture and storage demonstration projects     

Nils Markusson  Atsushi Ishii 《Global Environmental Change》2011,21(2):293-302

Demonstration of a fully integrated power plant with carbon capture and storage (CCS) at scale has not yet been achieved, despite growing international political interest in the potential of the technology to contribute to climate change mitigation and calls from multiple constituents for more demonstration projects. Acknowledging the scale of learning that still must occur for the technology to advance towards deployment, multiple CCS demonstration projects of various scales are emerging globally. Current plans for learning and knowledge sharing associated with demonstration projects, however, seem to be limited and narrowly conceived, raising questions about whether the projects will deliver on the expectations raised. Through a comparison of the structure, framing and socio-political context of three very different CCS demonstration projects in different places and contexts, this paper explores the complexity of social learning associated with demonstration projects. Variety in expectations of the demonstration projects’ objectives, learning processes, information sharing mechanisms, public engagement initiatives, financing and collaborative partnerships are highlighted. The comparison shows that multiple factors including the process of building support for the project, the governance context and the framing of the project matter for the learning in demonstration projects. This analysis supports a broader conceptualization of learning than that currently found in CCS demonstration plans - a result with implications for both future research and practice.  相似文献   

Co-management and the co-production of knowledge: Learning to adapt in Canada's Arctic   总被引：3，自引：0，他引：3  

Derek Armitage  Fikret BerkesAaron Dale  Erik Kocho-SchellenbergEva Patton 《Global Environmental Change》2011,21(3):995-1004

Co-management institutional arrangements have an important role in creating conditions for social learning and adaptation in a rapidly changing Arctic environment, although how that works in practice has not been clearly articulated. This paper draws on three co-management cases from the Canadian Arctic to examine the role of knowledge co-production as an institutional trigger or mechanism to enable learning and adapting. Experience with knowledge co-production across the three cases is variable but outcomes illustrate how co-management actors are learning to learn through uncertainty and environmental change, or learning to be adaptive. Policy implications of this analysis are highlighted and include the importance of a long-term commitment to institution building, an enabling policy environment to sustain difficult social processes associated with knowledge co-production, and the value of diverse modes of communication, deliberation and social interaction.  相似文献   

《国际汉语能力标准》中值得商榷的地方——兼与《欧洲语言共同参考框架:学习、教学、评估》比较     

徐海冰  程燕 《广东海洋大学学报》2011,31(5):91-95

通过对《国际汉语能力标准》的考察,同时与《欧洲语言共同参考框架:学习、教学、评估》比较,发现《国际汉语能力标准》存在三个方面的问题:结构不合理、内容有缺失以及评级等级标准不科学,以此研究结果为《国际汉语能力标准》的修订提供参考。  相似文献   

Site characterization model using least‐square support vector machine and relevance vector machine based on corrected SPT data (Nc)     

Pijush Samui  T. G. Sitharam 《国际地质力学数值与分析法杂志》2010,34(7):755-770

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N_c), N values have been corrected (N_c) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three‐dimensional site characterization model, the function N_c=N_c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N_c value, is to be approximated in which N_c value at any half‐space point in Bangalore can be determined. The first algorithm uses least‐square support vector machine (LSSVM), which is related to a ridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel‐based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

发现学习在《GPS定位技术》教学中的应用研究   总被引：2，自引：0，他引：2  

王坚  高井祥  唐艳梅  许长辉  彭祥国 《测绘信息与工程》2010,35(2):48-49

论述了发现式学习与教学的概念，提出了采用发现学习的方法进行《GPS定位技术》教学的可行性，分析了基于发现学习的教学设计和具体内容，指出了发现学习存在的不足。  相似文献   

软件模块故障倾向预测方法研究   总被引：2，自引：0，他引：2  

罗云锋  普杰  贲可荣 《武汉大学学报(信息科学版)》2010,(5)

研究了在区分故障严重程度下的软件模块故障倾向预测方法,将故障分为高严重程度和低严重程度两种类型,用统计分析和机器学习方法分析静态代码度量与故障倾向之间的关系。以公开和私有两种类型的失效数据集作为实验数据,分析发现,故障的严重程度影响预测性能,预测不同严重程度的故障需要选择不同的度量和分类模型,预测低严重程度故障的性能好于预测高严重程度故障的性能。  相似文献   

Simulation of site-scale water fluxes in desert and natural oasis ecosystems of the arid region in Northwest China     

Mingjuan Xie  Geping Luo  Olaf Hellwich  Amaury Frankl  Wenqiang Zhang  Chunbo Chen  Chen Zhang  Philippe De Maeyer 《水文研究》2021,35(12):e14444

The study of water fluxes is important to better understand hydrological cycles in arid regions. Data-driven machine learning models have been recently applied to water flux simulation. Previous studies have built site-scale simulation models of water fluxes for individual sites separately, requiring a large amount of data from each site and significant computation time. For arid areas, there is no consensus as to the optimal model and variable selection method to simulate water fluxes. Using data from seven flux observation sites in the arid region of Northwest China, this study compared the performance of random forest (RF), support vector machine (SVM), back propagation neural network (BPNN), and multiple linear regression (MLR) models in simulating water fluxes. Additionally, the study investigated inter-annual and seasonal variation in water fluxes and the dominant drivers of this variation at different sites. A universal simulation model for water flux was built using the RF approach and key variables as determined by MLR, incorporating data from all sites. Model performance of the SVM algorithm (R² = 0.25–0.90) was slightly worse than that of the RF algorithm (R² = 0.41–0.91); the BPNN algorithm performed poorly in most cases (R² = 0.15–0.88). Similarly, the MLR results were limited and unreliable (R² = 0.00–0.66). Using the universal RF model, annual water fluxes were found to be much higher than the precipitation received at each site, and natural oases showed higher fluxes than desert ecosystems. Water fluxes were highest during the growing season (May–September) and lowest during the non-growing season (October–April). Furthermore, the dominant drivers of water flux variation were various among different sites, but the normalized difference vegetation index (NDVI), soil moisture and soil temperature were important at most sites. This study provides useful insights for simulating water fluxes in desert and oasis ecosystems, understanding patterns of variation and the underlying mechanisms. Besides, these results can make a contribution as the decision-making basis to the water management in desert and oasis ecosystems.  相似文献   

Radial Basis Functional Link Nets Used as a Prospectivity Mapping Tool for Orogenic Gold Deposits Within the Central Lapland Greenstone Belt, Northern Fennoscandian Shield   总被引：1，自引：0，他引：1  

Vesa Nykänen 《Natural Resources Research》2008,17(1):29-48

Among the more popular spatial modeling techniques, artificial neural networks (ANN) are tools that can deal with non-linear relationships, can classify unknown data into categories by using known examples for training, and can deal with uncertainty; characteristics that provide new possibilities for data exploration. Radial basis functional link nets (RBFLN), a form of ANN, are applied to generate a series of prospectivity maps for orogenic gold deposits within the Paleoproterozoic Central Lapland Greenstone Belt, Northern Fennoscandian Shield, Finland, which is considered highly prospective yet clearly under explored. The supervised RBFLN performs better than previously applied statistical weights-of-evidence or conceptual fuzzy logic methods, and equal to logistic regression method, when applied to the same geophysical and geochemical data layers that are proxies for conceptual geological controls. By weighting the training feature vectors in terms of the size of the gold deposits, the classification of the neural network results provides an improved prediction of the distribution of the more important deposits/occurrences. Thus, ANN, more specifically RBFLN, potentially provide a better tool to other methodologies in the development of prospectivity maps for mineral deposits, hence aiding conceptual exploration.  相似文献   

移动互联网时代防震减灾科普宣传的问题及对策研究     

李晓丽 《高原地震》2014,(1):54-58

在移动互联网蓬勃发展的信息技术背景下,我国防震减灾科普教育存在若干问题,如忽视受众的"数字化"特征,基于智能终端的宣传材料不足;宣传手段不能满足移动互联网时代信息化要求;宣传内容不够生动等,因此提出防震减灾科普知识泛在化宣传新模式,并根据泛在化宣传模式的特征,设计开发基于iOS系统的泛在化宣传资源,为防震减灾宣传工作提供基于移动设备的数字化资源支持。该研究对移动互联网时代地震科普宣传作了新的探讨与尝试,对于当前及未来全民普及防震减灾科学知识有积极的促进作用。  相似文献   

Banach空间中非扩张映像的强收敛性     

李全刚 《成都信息工程学院学报》2010,25(3):321-323

在实光滑和一致凸Banach空间中通过引入广义度量投影,证明了一个关于非扩张映像的修正Mann迭代序列的强收敛性定理。目的是利用广义度量投影来修改Nakajo与Takahashi的迭代方案,并将Nakajo与Taka—hashi文中所对应的主要结果由Hilbert空间推广到实光滑和一致凸Banach空间。  相似文献