基于交叉验证的多模式超级集合预报方法研究

利用AREM、MM5和WRF 3个中尺度有限区域模式,通过选取对短期天气预报影响颇大的积云参数化方案和边界层方案构成15个集合预报成员,以2003年7月汛期天气为研究对象,分别采用相关加权、多元线性回归以及支持向量机回归与"交叉验证"相结合的方法,开展有限区域模式的多模式短期超级集合预报研究.文中主要对上述3种方法的24 h降水和700 hPa流场的超级集合预报结果与多模式集合平均预报结果以及T213模式结果进行了对比分析,结果表明:(1)对于24 h降水,支持向量机回归方法的超级集合预报得到的均方根误差比多模式集合平均小,各降水临界值的TS异常评分比多模式集合平均高;并且它也较相关加权法和多元线性回归的超级集合预报效果好.(2)对于700 hPa流场,对比分析各预报结果经过向量EOF分析得到的风场第1模态和第2模态表明,多模式集合平均主要使风场强度变小,多元线性回归和支持向量机回归的超级集合预报可以较好地刻画风场的强度分布,其中支持向量机回归的超级集合预报对风场强度及其区域分布的预报效果最好.(3)对于700 hPa流场,超级集合预报明显优于同期T213模式预报,从相同的预报均方根误差意义看,支持向量机回归的超级集合预报至少较T213模式预报能提前12 h.     

Computation of the safety factor for slope stability using discontinuous deformation analysis and the vector sum method

This study introduces the vector sum method into discontinuum-based methods by considering the sliding vector and the stress state of the discrete block system. The sliding direction computation and force projection in the new approach are detailed, and the safety factor is solved by explicit equations. The vector sum method is implemented in the discontinuous deformation analysis (DDA) program and is used to compute the safety factors for two numerical examples. A comparison of the solutions obtained with the theoretical analysis and limit equilibrium analysis demonstrates that the new method is suitable for calculating the safety factor of a slope.     

Pioneering patterns of ballast treatment in the emerging era of marine vector management

Human-mediated transfer and invasions of organisms have permanently altered distribution patterns on a global scale. In response to growing numbers and impacts of invasions, global-scale vector management is advancing to curtail unintentional and unwanted species re-distributions. In marine systems, ocean-going ships have been the major dispersal mechanism across biogeographic barriers, and maritime vector management has become a priority global initiative, including national regulations and recent ratification of an international convention to manage ballast water. This paper provides the first analysis of the pioneering patterns of ballast water treatment systems (BWTS) on board commercial ships, using vessel arrivals to the United States as a model system. Over an opening 28-month period, >200 unique vessels arriving to the U.S. reported BWTS operations, using 58 different systems to treat 4.42 million m³ of discharged ballast water. Although this volume represents <2% of all ballast water discharged in the U.S. per month during this period, there was substantial growth in treated ballast discharge throughout this time. Through 2015, ‘Filtration+UV’ systems were the most common BWTS type installed across all ship types. Currently, BWTSs occur on higher numbers of tankers and bulkers, but a higher proportion of passenger vessels, than other ship types. If BWTSs meet the required discharge standards as intended, this will cause a steep reduction in total discharge of organisms ≥50 µm compared to current practices. While several hurdles in fleet-wide BWTS adoption remain, including the timeline for BWTS installation across the global fleet, we are at a significant milestone in the history and evolution of global shipping, which is undergoing wholesale transition to a new and more effective global-scale ballast vector management strategy.     

基于RBF和PSO的双喉道气动矢量喷管优化设计

本文探索了一种能多变量综合优化的方法,即对喷管进行参数化设计后,用均匀试验设计(UED)将试验样本均匀散布在设计区间内,求出各性能参数后,利用径向基神经网络(RBF)对试验样本进行拟合,再用粒子群算法(PSO)对训练好的神经网络进行寻优,找出了更好的双喉道气动矢量喷管设计参数组合。数值模拟结果显示,优化后的双喉道气动矢量喷管的矢量角有了明显提高。试验表明这种优化方法具有很好的优化能力,可以用来对喷管几何外形进行参数优化。      

似大地水准面的支持向量机模型研究

支持向量机(SVM)是一种基于结构风险最小化原理的学习技术,也是一种新的具有较好泛化性能的回归方法。本文简要介绍了SVM原理,针对大面积复杂似大地水准面的确定问题,仅依据测区的GPS水准实测数据,利用SVM方法整体建模。通过工程实例并与神经网络模型进行对比,证实了SVM似大地水准面模型的可靠性。     

支持向量机非线性回归方法的气象要素预报

该文介绍了基于基本的支持向量机非线性回归方法,该方法具有解决非线性问题的能力,在数值预报解释应用技术中,对某些预报量与预报因子之间相关性不显著的要素,如风、比湿等,采用支持向量机非线性回归技术较多元回归的MOS方法更具优势;利用北京市气象局中尺度业务模式 (MM5V3) 的12:00(世界时) 起始数值预报产品和观测资料,制作北京15个奥运场馆站点6~48 h逐3 h的气象要素释用产品。对比MM5V3模式,从均方根误差的平均减小率来看,2 m温度减小12.1%,10 m风u分量减小43.3%,10 m风v分量减小53.4%,2 m比湿减小38.2%。与同期的MOS方法预报结果相比,整体预报效果SVM略优于MOS。由此可见,支持向量机非线性回归方法解决与预报因子之间非线性相关的气象要素较好,具有较高的预报优势。     

Future changes in rainfall,temperature and reference evapotranspiration in the central India by least square support vector machine

Climate change affects the environment and natural resources immensely. Rainfall, temperature and evapotranspiration are major parameters of climate affecting changes in the environment. Evapotranspiration plays a key role in crop production and water balance of a region, one of the major parameters affected by climate change. The reference evapotranspiration or ET₀ is a calculated parameter used in this research. In the present study, changes in the future rainfall, minimum and maximum temperature, and ET₀ have been shown by downscaling the HadCM3 (Hadley Centre Coupled Model version 3) model data. The selected study area is located in a part of the Narmada river basin area in Madhya Pradesh in central India. The downscaled outputs of projected rainfall, ET₀ and temperatures have been shown for the 21st century with the HADCM3 data of A2 scenario by the Least Square Support Vector Machine (LS-SVM) model. The efficiency of the LS-SVM model was measured by different statistical methods. The selected predictors show considerable correlation with the rainfall and temperature and the application of this model has been done in a basin area which is an agriculture based region and is sensitive to the change of rainfall and temperature. Results showed an increase in the future rainfall, temperatures and ET₀. The temperature increase is projected in the high rise of minimum temperature in winter time and the highest increase in maximum temperature is projected in the pre-monsoon season or from March to May. Highest increase is projected in the 2080s in 2081–2091 and 2091–2099 in maximum temperature and 2091–2099 in minimum temperature in all the stations. Winter maximum temperature has been observed to have increased in the future. High rainfall is also observed with higher ET₀ in some decades. Two peaks of the increase are observed in ET₀ in the April–May and in the October. Variation in these parameters due to climate change might have an impact on the future water resource of the study area, which is mainly an agricultural based region, and will help in proper planning and management.     

霍西煤矿区地表滑坡灾害敏感性数值建模与等级划分

本文以山西省霍西煤矿区为研究区,利用遥感和GIS方法对滑坡灾害的敏感性进行了数值建模与定量评价。利用交叉检验方法构建了径向基核函数支持向量机滑坡敏感性评价模型,并基于拟合精度对模型进行了定量评价;对各评价因子在模型中的重要性进行对比分析;基于空间分辨率为30m的评价因子,通过径向基核函数支持向量机模型获得了霍西煤矿区滑坡敏感性指数值,并利用分位数法将霍西煤矿区的滑坡敏感性分为极高、高、中和低4个等级。结果表明：拟合精度建模阶段和验证阶段分别为87.22%和70.12%;与滑坡敏感性关系最密切的5个评价因子依次是岩性、距道路距离、坡向、高程和土地利用类型;极高和高敏感区域分布了93.49%的滑坡点,面积占总面积的50.99%,是比较合理的分级方案。本研究不仅可以为研究区人工边坡调查和煤矿资源合理开采提供借鉴,对相似矿区的相关工作也具有参考价值。     

栅格式数据转换为矢量式数据的两个算法研究

本文探讨了如何把二值图像的细化算法推广应用于对多值图像的细化处理,提出了一种矢量式数据内部由连续曲线向图形特征点数据转换的逐段线性拟合方法。     

Iterative vector methods for computing geodetic latitude and height from rectangular coordinates

 Two iterative vector methods for computing geodetic coordinates (φ, h) from rectangular coordinates (x, y, z) are presented. The methods are conceptually simple, work without modification at any latitude and are easy to program. Geodetic latitude and height can be calculated to acceptable precision in one iteration over the height range from −10⁶ to +10⁹ m. Received: 13 December 2000 / Accepted: 13 July 2001