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In this study, the climate teleconnections with meteorological droughts are analysed and used to develop ensemble drought prediction models using a support vector machine (SVM)–copula approach over Western Rajasthan (India). The meteorological droughts are identified using the Standardized Precipitation Index (SPI). In the analysis of large‐scale climate forcing represented by climate indices such as El Niño Southern Oscillation, Indian Ocean Dipole Mode and Atlantic Multidecadal Oscillation on regional droughts, it is found that regional droughts exhibits interannual as well as interdecadal variability. On the basis of potential teleconnections between regional droughts and climate indices, SPI‐based drought forecasting models are developed with up to 3 months' lead time. As traditional statistical forecast models are unable to capture nonlinearity and nonstationarity associated with drought forecasts, a machine learning technique, namely, support vector regression (SVR), is adopted to forecast the drought index, and the copula method is used to model the joint distribution of observed and predicted drought index. The copula‐based conditional distribution of an observed drought index conditioned on predicted drought index is utilized to simulate ensembles of drought forecasts. Two variants of drought forecast models are developed, namely a single model for all the periods in a year and separate models for each of the four seasons in a year. The performance of developed models is validated for predicting drought time series for 10 years' data. Improvement in ensemble prediction of drought indices is observed for combined seasonal model over the single model without seasonal partitions. The results show that the proposed SVM–copula approach improves the drought prediction capability and provides estimation of uncertainty associated with drought predictions. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
63.
When travelling, people are accustomed to taking and uploading photos on social media websites, which has led to the accumulation of huge numbers of geotagged photos. Combined with multisource information (e.g. weather, transportation, or textual information), these geotagged photos could help us in constructing user preference profiles at a high level of detail. Therefore, using these geotagged photos, we built a personalised recommendation system to provide attraction recommendations that match a user's preferences. Specifically, we retrieved a geotagged photo collection from the public API for Flickr (Flickr.com) and fetched a large amount of other contextual information to rebuild a user's travel history. We then created a model-based recommendation method with a two-stage architecture that consists of candidate generation (the matching process) and candidate ranking. In the matching process, we used a support vector machine model that was modified for multiclass classification to generate the candidate list. In addition, we used a gradient boosting regression tree to score each candidate and rerank the list. Finally, we evaluated our recommendation results with respect to accuracy and ranking ability. Compared with widely used memory-based methods, our proposed method performs significantly better in the cold-start situation and when mining ‘long-tail’ data. 相似文献
64.
We performed an in-depth literature survey to identify the most popular data mining approaches that have been applied for raster mapping of ecological parameters through the use of Geographic Information Systems (GIS) and remotely sensed data. Popular data mining approaches included decision trees or “data mining” trees which consist of regression and classification trees, random forests, neural networks, and support vector machines. The advantages of each data mining approach as well as approaches to avoid overfitting are subsequently discussed. We also provide suggestions and examples for the mapping of problematic variables or classes, future or historical projections, and avoidance of model bias. Finally, we address the separate issues of parallel processing, error mapping, and incorporation of “no data” values into modeling processes. Given the improved availability of digital spatial products and remote sensing products, data mining approaches combined with parallel processing potentials should greatly improve the quality and extent of ecological datasets. 相似文献
65.
This paper aims to present the critical top tension for static equilibrium configurations of a steel catenary riser(SCR) by using the finite element method. The critical top tension is the minimum top tension that can maintain the equilibrium of the SCR. If the top tension is smaller than the critical value, the equilibrium of the SCR does not exist. If the top tension is larger than the critical value, there are two possible equilibrium configurations. These two configurations exhibit the nonlinear large displacement. The configuration with the smaller displacement is stable, while the one with larger displacement is unstable. The numerical results show that the increases in the riser's vertical distances, horizontal offsets, riser's weights, internal flow velocities, and current velocities increase the critical top tensions of the SCR. In addition, the parametric studies are also performed in order to investigate the limit states for the analysis and design of the SCR. 相似文献
66.
为分析南海北部海域油气勘探保障建设选址的适宜性,在广泛研究备选区特征资料的基础上,基于层次分析法(Analytic Hierarchy Process, AHP)原理,以自然环境因素、开发环境因素、基础设施与投资情况以及其他因素作为一级评判准则,建立了包括12项二级评判准则的递进层次结构模型,并以永兴岛、赵述岛和晋卿岛作为3个假定备选区,来验证分析评价模型的有效性和可靠性。AHP评判结果显示,3个备选区的整体优劣指数依次为0.587 1, 0.212 1, 0.200 8;AHP模型的一致性比例CR值为0.020 3。通过分析和筛选影响远海油气勘探保障建设的选址因子,构建基于AHP原理的选址评价模型,可用于分析评价南海北部岛礁油气勘探保障建设选址的适宜性。 相似文献
67.
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 (Nc), N values have been corrected (Nc) 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 Nc=Nc (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to Nc value, is to be approximated in which Nc 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
68.
城市规划领域越来越需要三维建模技术的支持。CityEngine作为一种新型的三维建模软件,不仅可以批量生成规划模型,还可以用来辅助三维城市规划设计。本文基于CityEngine规则建模方法,实现了规划方案对比、建筑体量调整、规划指标计算等功能,通过对某小区进行实际建模验证,证明了CityEngine可以为城市规划者们提供新的思路,为城市设计和城市管理提供决策支持。 相似文献
69.
目前,基层台站在雷暴预警预报中主要依赖传统经验预报方法,而对卫星云图、大气电场、多普勒雷达回波和高分辨率数值预报产品等资料释用水平不高,存在主观定性分析多、客观定量计算少等不足。依托现有气象资料和雷暴预报方法,以雷暴预警预报系统构建为目标,从气象数据仓库构建、支持向量机雷暴预报、相似预报雷暴预报、Poor Man集合预报技术和多源数据融合分析等方面,探讨了雷暴预警预报系统构建方法,实现了雷暴中期预测、短期预报和短时临近预警三个层次的预报功能,解决了气象资料庞杂难以管理、数值预报产品释用水平不高、数值预报结果存在"跃变"、多源数据融合分析缺乏手段等问题,提高了基层台站雷暴预报工作效率和预报水平,同时也为其他地区类似系统构建提供了参考。 相似文献
70.