基于扩展集合操作的频繁项集挖掘算法研究

对传统集合操作进行了扩展，提出了基于扩展集合操作的最大频繁项集生成算法FIS-ES，并从理论上对算法的复杂度进行了详细的分析。实验表明，在最小支持度较小的情况下，FIS-ES算法比Apriori算法具有更快的挖掘速度、更少的空间占用等优点，与Apriori有很好的互补性。     

3D wavefield extrapolation with optimal separable approximation

An accurate and wide-angle one-way propagator for wavefield extrapolation is an important topic for research on wave-equation prestack depth migration in the presence of large and rapid velocity variations. Based on the optimal separable approximation presented in this paper, the mixed domain algorithm with forward and inverse Fourier transforms is used to construct the 3D one-way wavefield extrapolation operator. This operator separates variables in the wavenumber and spatial domains. The phase shift operation is implemented in the wavenumber domain while the time delay for lateral velocity variation is corrected in the spatial domain. The impulse responses of the one-way wave operator show that the numeric computation is consistent with the theoretical value for each velocity, revealing that the operator constructed with the optimal separable approximation can be applied to lateral velocity variations for the case of small steps. Imaging results of the SEG/EAGE model and field data indicate that the new method can be used to image complex structure.     

Comparison of forecasting performance of nonlinear models of hydrological time series

Mean monthly flows of the Tatry alpine mountain region in Slovakia are predominantly fed by snowmelt in the spring and convective precipitation in the summer. Therefore their regime properties exhibit clear seasonal patterns. Positive deviations from these trends have substantially different features than the negative ones. This provides intuitive justification for the application of nonlinear two-regime models for modelling and forecasting of these time series. Nonlinear time series structures often have lead to good fitting performances, however these do not guarantee an equally good forecasting performance. In this paper therefore the forecasting performance of several nonlinear time series models is compared with respect to their capabilities of forecasting monthly and seasonal flows in the Tatry region. A new type of regime-switching models is also proposed and tested. The best predictive performance was achieved for a new model subclass involving aggregation operators.     

位场数据网格化的反插值法

位场不规则分布数据的网格化是位场数据分析处理的首要问题.本文借鉴反插值法的原理，提出利用基于预条件共轭梯度的反插值法实现位场数据的网格化.其中，插值算子采用高斯权系数，滤波算子采用Laplacian算子，预条件算子采用滤波算子的逆.通过理论模型和实际航磁数据的网格化试验分析，验证了本文的反插值法适合地球物理位场特征，网格化速度快，精度高，效果好.     

Current Status and Future Challenges of Weather Radar Polarimetry: Bridging the Gap between Radar Meteorology/Hydrology/Engineering and Numerical Weather Prediction

After decades of research and development, the WSR-88 D(NEXRAD) network in the United States was upgraded with dual-polarization capability, providing polarimetric radar data(PRD) that have the potential to improve weather observations,quantification, forecasting, and warnings. The weather radar networks in China and other countries are also being upgraded with dual-polarization capability. Now, with radar polarimetry technology having matured, and PRD available both nationally and globally, it is important to understand the current status and future challenges and opportunities. The potential impact of PRD has been limited by their oftentimes subjective and empirical use. More importantly, the community has not begun to regularly derive from PRD the state parameters, such as water mixing ratios and number concentrations, used in numerical weather prediction(NWP) models.In this review, we summarize the current status of weather radar polarimetry, discuss the issues and limitations of PRD usage, and explore potential approaches to more efficiently use PRD for quantitative precipitation estimation and forecasting based on statistical retrieval with physical constraints where prior information is used and observation error is included. This approach aligns the observation-based retrievals favored by the radar meteorology community with the model-based analysis of the NWP community. We also examine the challenges and opportunities of polarimetric phased array radar research and development for future weather observation.     

基于IOWA算子的RFID数据有效性评价方法

智能交通系统应用的迅猛发展需要高质量的交通数据,而交通数据采集技术采集到的原始数据会不可避免地混入异常数据,降低数据的有效性,从而可能引起系统应用性能的降低.本文针对基于无线射频技术（RFID）的交通数据,设计了一套交通数据评价指标,并根据交通数据评价指标的特点,综合评价权重向量计算方法的适用条件及优缺点,建立了基于IOWA（Induced Ordered Weighted Averaging）算子的交通数据综合评价方法.基于实际数据的分析结果表明,该方法可以对RFID交通数据进行有效性评价.     

结合Forstner与NCC约束的UAV图像配准研究

随着无人机(unmanned aerial vehicle,UAV)技术的飞快发展,UAV已成为航空遥感图像获取的重要手段。但与传统的大飞机航空摄影相比,UAV在平台的稳定性方面较差,采集图像时受自身配重、即时飞行环境等外界因素影响,使得最终获得的遥感图像存在复杂的几何变形,导致其图像配准过程存在很大的困难。针对此问题,首先基于UAV的POS数据进行图像重叠区域估算,利用Forstner算子提取图像中的特征点并结合信息熵对图像进行分块处理;然后通过基于旋转的归一化互相关(normalized cross-correlation,NCC)系数寻找相匹配的同名特征点,最终实现UAV图像的配准。实验结果证明该方法切实有效,并且保持了较好的鲁棒性。     

一类非线性奇异边值问题解的存在性

证明一类非线性奇异边值问题解的存在性定理,改进了Ｄｕｎｎｉｎｇｅｒ和Ｋｕｒｔｚ的结果,构造具体的方程说明存在性定理中的条件不能去掉,这表明［４］中一结果不真。     

基于数学形态学细化算子的改进Canny算法研究

边缘检测是图像处理领域研究的一个重要内容。本文基于数学形态学改进现有Canny算子。该方法首先用Canny算子进行滤波,然后采用非极大抑制技术,将强边缘图像和弱边缘图像的边缘进行连接,再对提取的边缘利用形态学细化算子细化。针对不同图像采用不同门限比例,可取得不同的边缘提取效果。本文采用峰值信噪比、均方误差、平均绝对误差三个评价指标对边缘检测算法的优越性进行度量。实验分析表明,本文算法优于Sobel算子、Roberts算子、Log算子及传统Canny算法。     

基于Gabor框架合成小波束叠前深度偏移

利用小波束域波场分解和传播在空间及方向上的双重局域性,通过Fourier传播算子进行深度外推波场,完成小波束的传播,最终应用成像条件求取成像值.合成小波束和小束源记录,进行部分小束源叠前偏移成像的数值试验,获得的成像结果表明,小波束叠前深度成像是切实有效的.