陕西省道路线性参考数据集的生产与思考

利用线性数据的线性运算特性,以2018年“天地图?陕西”电子地图中的道路数据为基础,结合交通部门的相关专业数据资料和采集的高速里程桩号数据,制作陕西省道路线性参考数据集。将天地图道路数据以道路线性参考数据集的形式进行存储和生产,可对道路数据进行桩号定位服务,有利于道路定位、查找等功能的应用,对交通部门、应急管理部门等相关部门提供了快速、准确的服务。

基于核函数距离测度的LLE降维及其在离群聚类中的应用

局部线性嵌入算法(locally linear embedding,LLE)是一种流形降维方法,在高维稀疏数据空间中,针对LLE不适合稀疏采样和欧氏距离公式的缺陷,研究该算法的扩展,引入核函数,并将样本映射到高维特征空间,核映射改善了样本的空间分布,改进的LLE方法在适当选取近邻点个数情况下,可得到良好的效果。对从高维采样数据中恢复得到低维数据集,通过本文提出的离群数据假设,并结合本文给出的离群聚类方法对所得低维数据是否是离群数据进行判别。仿真文验的结果表明了该方法能够有效地发现高维数据集中的离群点,与此同时,该算法具有参数估计简单、参数影响不大等优点,该算法为离群点检测问题的机器学习提供了一条新的途径。

概论核方法及核参数的选择

本文介绍支持向量机分类非线性数据集的优越性,讨论了基于核的方法,并对核的方法的实质进行了论述。通过matlab制作的图像可知:核方法的参数的选择对于基于核的分类法具有重要作用。对现有的选择核参数的方式效果进行了归纳与比较,从而分析得出了各种选择参数方式的优缺点。

基于支持向量机(SVM)算法的加工机械故障分析

针对工业领域中加工机械故障数据集的复杂性和海量性,对经典支持向量机(SVM)算法进行深度优化,引入规范化超平面分割数据集,并求解最优解;选择高斯径向基函数作为算法模型核函数,改善算法的泛化性能;基于样本熵排列方式提取故障信号特征,在不可分空间内也可以实现对非线性数据集的精确分割。仿真结果与实例验证表明,优化SVM算法具有更强的数据集分类性能和故障分析与检测性能,实际应用效果良好。

Evaluating the impact of spatio-temporal scale on CPUE standardization

This study focused on the quantitative evaluation of the impact of the spatio-temporal scale used in data collection and grouping on the standardization of CPUE(catch per unit effort).We used the Chinese squid-jigging fishery in the northwestern Pacific Ocean as an example to evaluate 24 scenarios at different spatio-temporal scales,with a combination of four levels of temporal scale(weekly,biweekly,monthly,and bimonthly)and six levels of spatial scale(longitude×latitude:0.5°×0.5°,0.5°×1°,0.5°×2°,1°×0.5°,1°×1°,and 1°×2°).We applied generalized additive models and generalized linear models to analyze the24 scenarios for CPUE standardization,and then the differences in the standardized CPUE among these scenarios were quantified.This study shows that combinations of different spatial and temporal scales could have different impacts on the standardization of CPUE.However,at a fine temporal scale(weekly)different spatial scales yielded similar results for standardized CPUE.The choice of spatio-temporal scale used in data collection and analysis may create added uncertainty in fisheries stock assessment and management.To identify a cost-effective spatio-temporal scale for data collection,we recommend a similar study be undertaken to facilitate the design of effective monitoring programs.

Advanced Irrigation Engineering： Precision and Precise

Irrigation advances in precision irrigation （PI） or site specific irrigation （SSI） have been considerable in research; however, commercialization lags. SSI/PI has applications when soil texture variability affects soil water holding capacity or when crop yield or biotic stresses （insects or diseases） are spatially variable. SSI/PI uses variable rate application technologies, mainly with center-pivots or lateral-move or linear irrigation machines, to match crop needs or soil water holding constraints. Variable rate applications are achieved by variable nozzle flow rates, pulsing nozzle flows, or multiple nozzles on separate submains. Newer center pivot and linear machines are controlled by on-board microprocessor systems that can be integrated with supervisory control and data acquisition controllers for both communication and control of the variable rate application for specific sets of nozzles or individual nozzles for management zones. Communication for center pivot or linear controllers typically uses radio telemetry, wireless interact links, or cellular telephones. Precision irrigation has limited utility without precise irrigation scheduling （temporally and spatially）. Plant or soil sensors are used to initiate or complete an irrigation event. Automated weather stations provide site information for determining the irrigation requirement using crop models or simpler reference evapotranspiration （ET）, data to be used with crop coefficients. Remote sensing is being used to measure crop water status or crop development from spectral reflectance. Near-surface remote sensing with sensors mounted on moving irrigation systems provide critical spatial integration from point weather networks and feedback on crop ET and irrigation controls in advanced automated systems for SSI/PI.

Geostrophic meridional transport in tropical Northwest Pacific based on Argo profiles

Absolute geostrophic currents in the North Pacific Ocean were calculated using P-vector method from newly gridded Argo profiling float data collected during 2004-2009. The meridional volume transport of geostrophic currents differed significantly from the classical Sverdrup balance, with differences of 10×106 -20×106 m3 /s in the interior tropical Northwest Pacific Ocean. Analyses showed that errors of wind stress estimation could not explain all of the differences. The largest differences were found in the areas immediately north and south of the bifurcation latitude of the North Equatorial Current west of the dateline, and in the recirculation area of the Kuroshio and its extension, where nonlinear eddy activities were robust. Comparison of the geostrophic meridional transport and the wind-driven Sverdrup meridional transport in a high-resolution OFES simulation showed that nonlinear effects of the ocean circulation were the most likely reason for the differences. It is therefore suggested that the linear, steady wind-driven dynamics of the Sverdrup theory cannot completely explain the meridional transport of the interior circulation of the tropical Northwest Pacific Ocean.

Effect of Recycled Coarse Aggregate on Concrete Compressive Strength

The effect of recycled coarse aggregate on concrete compressive strength was investigated based on the concrete skeleton theory. For this purpose, 30 mix proportions of concrete with target cube compressive strength ranging from 20 to 60 MPa were cast with normal coarse aggregate and recycled coarse aggregate from different strength parent concretes. Results of 28-d test show that the strength of different types of recycled aggregate affects the concrete strength obviously. The coarse aggregate added to mortar matrix plays a skeleton role and improves its compressive strength. The skeleton effect of coarse aggregate increases with the increasing strength of coarse aggregate, and normal coarse aggregate plays the highest, whereas the lowest concrete strength occurs when using the weak recycled coarse aggregate. There is a linear relationship between the concrete strength and the corresponding mortar matrix strength. Coarse aggregate skeleton formula is established, and values from experimental tests match the derived expressions.

Corrected-loss estimation for Error-in-Variable partially linear model

We consider an Error-in-Variable partially linear model where the covariates of linear part are measured with error which follows a normal distribution with a known covariance matrix. We propose a corrected-loss estimation of the covariate effect. The proposed estimator is asymptotically normal. Simulation studies are presented to show that the proposed method performs well with finite samples, and the proposed method is applied to a real data set.

Investigate the nonuniformity of low-energy electron beam with large cross-sections

Over the past decades, low-energy electron accelerators have been used worldwide for surface curing and sterilization. The beam nonuniformity is an important parameter of the low-energy electron beam with large cross-sections. A simple and accurate measurement system of nonuniformity for the low-energy electron beam with large cross-sections was developed. The main concept consists in the measurement of nonuniformity, which is realized by using a linear actuator to drive two scanning wires through the beam's cross-sections at a fixed speed. The beam distribution can be obtained by sending/collecting the current signals to/from the Data Acquisition (DAQ) software on a laptop by a USB DAQ card. This device is very convenient for the performance testing of a new accelerator at the manufacturer's site. The distribution of the homemade low voltage electron accelerator EBS-300-50 was measured and evaluated.

An improved HASM method for dealing with large spatial data sets

Surface modeling with very large data sets is challenging. An efficient method for modeling massive data sets using the high accuracy surface modeling method(HASM) is proposed, and HASM_Big is developed to handle very large data sets. A large data set is defined here as a large spatial domain with high resolution leading to a linear equation with matrix dimensions of hundreds of thousands. An augmented system approach is employed to solve the equality-constrained least squares problem(LSE) produced in HASM_Big, and a block row action method is applied to solve the corresponding very large matrix equations.A matrix partitioning method is used to avoid information redundancy among each block and thereby accelerate the model.Experiments including numerical tests and real-world applications are used to compare the performances of HASM_Big with its previous version, HASM. Results show that the memory storage and computing speed of HASM_Big are better than those of HASM. It is found that the computational cost of HASM_Big is linearly scalable, even with massive data sets. In conclusion,HASM_Big provides a powerful tool for surface modeling, especially when there are millions or more computing grid cells.