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1.
利用2016年5月—2017年4月赤水市境内复兴驿站、古迹驿站及相邻县市内共6个大气负氧离子自动观测点和气象站的观测资料,分析了赤水市大气负氧离子浓度的时空变化特征及其与气象因子的关系。参照世界卫生组织制定的空气负氧离子等级标准,区划赤水市空气负氧离子的等级。结果表明:(1)赤水市日均大气负氧离子浓度5 056个/m3,高于临近县市的负氧离子浓度,白天略高于夜间,远超过负氧离子含量的一级标准;(2)年均大气负氧离子浓度为5 125个/m3,各季节浓度相差不大;(3)赤水市大气负氧离子浓度空间分布规律为复兴站古迹站,景区大于街道;与邻近县市比较,植被覆盖率大的区域大气负氧离子浓度高于植被覆盖率小的区域;(4)不同天气条件下大气负氧离子与气象因子的相关性不同。在雨日,大气负氧离子与气温、气压、水汽压相关;无雨日,大气负氧离子与日照相关;同时,白天雨相对于大气负氧离子浓度的增加较夜雨更为明显。 相似文献
2.
Application of support vector machine and relevance vector machine to determine evaporative losses in reservoirs 总被引：1，自引：0，他引：1
This article employs Support Vector Machine (SVM) and Relevance Vector Machine (RVM) for prediction of Evaporation Losses (E) in reservoirs. SVM that is firmly based on the theory of statistical learning theory, uses regression technique by introducing ε‐insensitive loss function has been adopted. RVM is based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. The input of SVM and RVM models are mean air temperature (T) ( °C), average wind speed (WS) (m/sec), sunshine hours (SH)(hrs/day), and mean relative humidity (RH) (%). Equations have been also developed for prediction of E. The developed RVM model gives variance of the predicted E. A comparative study has also been presented between SVM, RVM and ANN models. The results indicate that the developed SVM and RVM can be used as a practical tool for prediction of E. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
3.
Recent years have seen academic geographers engaged in a series of debates over the current state of the discipline, its ‘relevance’ to others in the social sciences, to policy-makers, and to those studying geography at school age. This short critical review builds upon an issue raised in this journal [Thrift, N., 2002. The future of geography. Geoforum 33, 291–298], namely the role of geographers as public intellectuals. After reviewing the different ways in which the notion of public intellectuals has been understood, the paper turns to geography’s representations and to its publics. The paper concludes by arguing for an appreciation of the full range of ways in which geographers call forth publics through a range of representational strategies. It suggests that regardless of how geographers perform publicly and intellectually, two things are perhaps worth remembering: it is in the interest of geographers to name what they do as geography and to name themselves as geographers. 相似文献
4.
Shivam Tripathi Rao S. Govindaraju 《Stochastic Environmental Research and Risk Assessment (SERRA)》2007,21(6):747-764
Recent advances in statistical learning theory have yielded tools that are improving our capabilities for analyzing large
and complex datasets. Among such tools, relevance vector machines (RVMs) are finding increasing applications in hydrology
because of (1) their excellent generalization properties, and (2) the probabilistic interpretation associated with this technique
that yields prediction uncertainty. RVMs combine the strengths of kernel-based methods and Bayesian theory to establish relationships
between a set of input vectors and a desired output. However, a bias–variance analysis of RVM estimates revealed that a careful
selection of kernel parameters is of paramount importance for achieving good performance from RVMs. In this study, several
analytic methods are presented for selection of kernel parameters. These methods rely on structural properties of the data
rather than expensive re-sampling approaches commonly used in RVM applications. An analytical expression for prediction risk
in leave-one-out cross validation is derived. For brevity, the effectiveness of the proposed methods is assessed first by
data generated from the benchmark sinc function, followed by an example involving estimation of hydraulic conductivity values
over a field based on observations. It is shown that a straightforward maximization of likelihood function can lead to misleading
results. The proposed methods are found to yield robust estimates of parameters for kernel functions. 相似文献
5.
Statistical downscaling of GCM simulations to streamflow using relevance vector machine 总被引：1，自引：0，他引：1
General circulation models (GCMs), the climate models often used in assessing the impact of climate change, operate on a coarse scale and thus the simulation results obtained from GCMs are not particularly useful in a comparatively smaller river basin scale hydrology. The article presents a methodology of statistical downscaling based on sparse Bayesian learning and Relevance Vector Machine (RVM) to model streamflow at river basin scale for monsoon period (June, July, August, September) using GCM simulated climatic variables. NCEP/NCAR reanalysis data have been used for training the model to establish a statistical relationship between streamflow and climatic variables. The relationship thus obtained is used to project the future streamflow from GCM simulations. The statistical methodology involves principal component analysis, fuzzy clustering and RVM. Different kernel functions are used for comparison purpose. The model is applied to Mahanadi river basin in India. The results obtained using RVM are compared with those of state-of-the-art Support Vector Machine (SVM) to present the advantages of RVMs over SVMs. A decreasing trend is observed for monsoon streamflow of Mahanadi due to high surface warming in future, with the CCSR/NIES GCM and B2 scenario. 相似文献
6.
利用印江县气象观测站1970～2018年汛期（5～9月）日降水量,日平均、最高和最低气温资料,采用线性倾向估计、滑动平均法、 Mann一Kendall趋势法、 Morlet小波分析等方法对印江县汛期降水年代际特征进行了研究,并采用相关分析、t 检验等方法研究汛期降水与气温的关系。结果表明：(1)印江县近49a汛期总降水量有不显著的增加趋势,呈现 “增加-减少”的交替年代变化特征。年代尺度演变上,20～35a,10～19a,7～9a以及2～4a的4类周期变化尺度共同起作用,其中27a为第一主周期,9a为第二主周期。（2）印江县近49a 6月、7月和8月对汛期总降水贡献最大,变化趋势和总降水量基本一致;小、中和大雨的年总降水量呈减少,其中中雨减少微弱;暴雨及以上有增加趋势。小和中雨所占百分比呈下降趋势,占百分比最多的大雨也呈下降趋势,但比较微弱,暴雨及以上有上升的趋势。（3）印江县近49a汛期总降水量与汛期最高温度、平均温度呈显著的负相关,月份上与8月最为密切, 7月次之,与其他月的温度相关性不大。不同量级降水量占总降水量的百分比,随日平均、最高气温的升高都呈先上升后下降的趋势,各量级降水的百分比的峰值都有各自的温度区间。 相似文献
7.
Precision agriculture requires high-resolution information to enable greater precision in the management of inputs to production. Actionable information about crop and field status must be acquired at high spatial resolution and at a temporal frequency appropriate for timely responses. In this study, high spatial resolution imagery was obtained through the use of a small, unmanned aerial system called AggieAirTM. Simultaneously with the AggieAir flights, intensive ground sampling for plant chlorophyll was conducted at precisely determined locations. This study reports the application of a relevance vector machine coupled with cross validation and backward elimination to a dataset composed of reflectance from high-resolution multi-spectral imagery (VIS–NIR), thermal infrared imagery, and vegetative indices, in conjunction with in situ SPAD measurements from which chlorophyll concentrations were derived, to estimate chlorophyll concentration from remotely sensed data at 15-cm resolution. The results indicate that a relevance vector machine with a thin plate spline kernel type and kernel width of 5.4, having LAI, NDVI, thermal and red bands as the selected set of inputs, can be used to spatially estimate chlorophyll concentration with a root-mean-squared-error of 5.31 μg cm−2, efficiency of 0.76, and 9 relevance vectors. 相似文献
8.
Nicholas J. Clifford 《Geoforum》2002,33(4):431-436
In a recent article, Thrift has presented an optimistic account of the future of Geography. While this reply is broadly supportive of his claims that Geography is more diverse, and has more to offer than ever before, it is less optimistic with respect to the prospects for the survival of Geography as a unitary academic discipline. Experiences over the last 20 years in the UK higher education, in particular, the 2001 RAE exercise, point to an unfavourable institutional climate for the discipline. Within Geography, the ever-increasing diversity of its subject matter and research philosophy poses problems for disciplinary identity. This is reflected in the more restricted perspective of the subject outside the universities, and is compounded by a weakening of the link between Geography in the universities and the schools. In these circumstances, serious attention must be given to the changing nature of the discipline, to its positioning with respect to other subjects, and to its relations with the wider world. At a time of academic, cultural, technological and social dynamism, there are, nevertheless, opportunities as well as dangers for the subject. Although this reply is an explicitly bleak one regarding the future, the implicit message is that Geography can (and should) still prosper. The more positive outcome, however, rests on an appreciation and nurturing of a more traditional geographical heritage than Thrift identifies, as well as a more creative view of the relationship between fundamental and applied research. 相似文献
9.
Our ability to deal with complex systems has improved through information system research which includes improved modeling
(both data and system), the use of semantics and advances in distributed computing. The past decade has seen an explosion
in the amount and variety of geosciences data and the emergence of true open data repositories through which scientists can
freely access this data. Those data are found in thousands of repositories located around the world. Virtual observatories
have been created to address the challenge of helping scientists search those repositories to find and access the required
data. This challenge is been addressed by using technologies such as the Internet (with ample connectivity and bandwidth),
the Web, cheap computing power, cheap storage and standards for critical components. Many scientific disciplines are developing
virtual observatories. Yet some of the most compelling science questions cross multiple domains. While semantics can provide
cross domain reasoning, often the first step in answering a question is determining what resources are available which may
be relevant to a topic. The topic can be expressed as simple phrases or word sequences. Using a common relevance scoring method
at all locations can enable a federated search across loosely coupled providers. The results of which can be organized into
facets to aid the user in selecting the most promising resources with which to pursue the scientific investigation. We describe
an approach to developing and deploying relevance scoring methods and faceted results in this brave new (virtual) world. We
have found that a scoring method which considers both the presence of terms and the proximity of these terms relative to the
order of the terms in the query improves the assessment of relevance. We call this Term Presence-Proximity (TPP) scoring and
describe a method for calculating a normalized score. TPP scoring compares favorably with other scoring approaches. 相似文献
10.
利用2005—2017年赤水国家气象观测站逐小时平均气温、相对湿度和10 min平均风速计算人体舒适度指数,对赤水人体舒适程度的气候特征进行了统计分析。结果表明,赤水舒适天气较多,存在少量的偏冷和炎热天气,酷热日数极少,具有显著的季节分布特征,具体为:①偏冷天气年日数在10～46 d之间波动,开始日期主要在12月份,占比85%,结束日期主要在2—3月份,偏冷天气出现在1月份的概率最大,一天中出现在04—11时的次数最多,出现在13—21时的次数较少;②酷热天气较少,仅出现6个时次,炎热天气年日数在16～54 d之间波动,在20～30 d的年度占比54%,炎热天气开始日期在6中旬—7月上旬,结束日期在8月中旬—9月下旬,一天中13—15时出现概率最大;③舒适天气年日数在135～176 d,年平均舒适天气152 d,4、5、9、10月是最舒适月份。研究表明,春秋季节较为舒适,适宜户外活动,也是赤水旅游的黄金期;冬季后半夜到上午易出现偏冷天气,夏季午后易出现炎热天气,户外活动时需要采取一定的防护措施。 相似文献