空间同位模式支持下城市服务业关联发现及特征分析

空间同位模式分析是数据挖掘中一种常见的方法,可有效挖掘城市设施在空间位置上的关联特征,进而发现城市设施的分布规律.本文基于POI数据同位模式挖掘用来获取城市服务业空间关联结构:首先,通过邻近实例获取、同位候选模式存储与筛选,得到城市服务业二阶同位模式;然后,据此构造产业空间关联图,得到产业间的关联结构;最后,分别构造了...     

Underground water quality model inversion of genetic algorithm

The underground water qualitymodel with non-linear inversion problem is illposed, and boils down to solving the minimum of nonlinear function. Genetic algorithms are adopted in a number of individuals of groups by iterative search to find the optimal solution of the problem, the encoding strings as its operational objective, and achieving the iterative calculations by the genetic operators. It is an effective method of inverse problems of groundwater, with incomparable advantages and practical significances.     

凸包插值算法的改进与实现

研究了凸包插值算法在n维欧拉空间构造Delaunay三角网的应用,提出了其三角剖分不惟一的重大缺陷,采用了限制区域生长法解决了这一缺陷。     

高精度高性价比的GPS定向仪的设计

介绍了一种高精度、高性价比的GPS定位定向仪的设计及实现（〈1mil,2σ）方法,系统利用了实际应用中的有利约束条件,对基于LAMBDA方法的载波相位整周模糊度解算算法进行了改进,经过系统工程设计,在实际应用中实现了单频、高精度、快速定向数据的输出。可以满足绝大多数环境下的使用需求,大大降低了系统成本。     

基于R树的分布式并行空间索引机制研究

为提高分布式并行计算环境下海量空间数据管理与并行化处理的效率,基于并行空间索引机制的研究,设计一种多层并行R树空间索引结构。该索引结构以高效率的并行空间数据划分策略为基础,以经典的并行计算方法论为依据,使其结构设计在保证能够获得较好的负载平衡性能的前提下,更适合于海量空间数据的并行化处理。以空间范围查询并行处理的系统响应时间为性能评估指标,通过实验证明并行空间索引结构具有设计合理、性能高效的特点。     

特征变量选择结合SVM的耕地土壤Hg含量高光谱反演

为探讨应用高光谱数据反演耕地土壤重金属汞(Hg)含量,对原始光谱进行10 nm重采样和SG平滑处理,用不同光谱变换数据与土壤重金属Hg含量进行相关性分析,采用IRIV、Random Frog和PCC提取光谱特征波段,分别建立SVM与GWO-SVM土壤Hg含量高光谱反演模型,获取Hg含量最优反演路径。研究表明,一阶微分变换光谱后土壤光谱特征更明显;上述特征提取方法在不同程度上减少光谱数据冗余,保留有效变量信息;经灰狼算法优化后支持向量机模型反演精度提高,IRIV结合GWO-SVM预测精度更高,其验证集R²为0.894,RMSE为0.082,MAE为0.016。研究成果可为类似土壤重金属含量的反演提供借鉴。     

A 3D discrete FEM iterative algorithm for solving the water pipe cooling problems of massive concrete structures

Water pipe cooling has been widely used for the temperature control and crack prevention of massive concrete structures such as high dams. Because both under‐cooling and over‐cooling may reduce the efficiency of crack prevention, or even lead to great harm to structures, we need an accurate and robust numerical tool for the prediction of cooling effect. Here, a 3D discrete FEM Iterative Algorithm is introduced, which can simulate the concrete temperature gradient near the pipes, as well as the water temperature rising along the pipes. On the basis of the heat balance between water and concrete, the whole temperature field of the problem can be computed exactly within a few iteration steps. Providing the pipe meshing tool for building the FE model, this algorithm can take account of the water pipe distribution, the variation of water flow, water temperature, and other factors, while the traditional equivalent algorithm based on semi‐theoretical solutions can only solve problems with constant water flow and water temperature. The validation and convergence are proved by comparing the simulated results and analytical solutions of two standard second‐stage cooling problems. Then, a practical concrete block with different cooling schemes is analyzed and the influences of cooling factors are investigated. In the end, detailed guidance for pipe system optimization is provided. Copyright © 2015 John Wiley & Sons, Ltd.     

Selection of sand models and identification of parameters using an enhanced genetic algorithm

Numerous constitutive models of granular soils have been developed during the last few decades. As a consequence, how to select an appropriate model with the necessary features based on conventional tests and with an easy way of identifying parameters for geotechnical applications has become a major issue. This paper aims to discuss the selection of sand models and parameters identification by using genetic algorithm. A real‐coded genetic algorithm is enhanced for the optimization with high efficiency. Models with gradually varying features (elastic‐perfectly plastic modelling, nonlinear stress–strain hardening, critical state concept and two‐surface concept) are selected from numerous sand models as examples for optimization. Conventional triaxial tests on Hostun sand are selected as the objectives in the optimization. Four key points are then discussed in turn: (i) which features are necessary to be accounted for in constitutive modelling of sand; (ii) which type of tests (drained and/or undrained) should be selected for an optimal identification of parameters; (iii) what is the minimum number of tests that should be selected for parameter identification; and (iv) what is the suitable and least strain level of objective tests to obtain reliable and reasonable parameters. Finally, a useful guide, based on all comparisons, is provided at the end of the discussion. Copyright © 2015 John Wiley & Sons, Ltd.     

Modelling combined open channel flow by artificial neural networks

Combined open channel flow is encountered in many hydraulic engineering structures and processes, such as irrigation ditches and wastewater treatment facilities. Extensive experimental studies have conducted to investigate combined flow characteristics. Nevertheless, there is no simple relationship that can fully describe the velocity profiles in a turbulent flow. The artificial neural network (ANN) has great computational capability for solving various complex problems, such as function approximation. The main objective of this study is to evaluate the applicability of the ANN for simulating velocity profiles, velocity contours and estimating the discharges accordingly. The velocity profiles measured by an acoustic doppler velocimeter in the open channel of the Chihtan purification plant, Taipei, with different discharges at fixed measuring section and different depths are presented. The total number of data sets is 640 and the data sets are split into two subsets, i.e. training and validation sets. The backpropagation algorithm is used to construct the neural network. The results demonstrate that the velocity profiles can be modelled by the ANN, and the ANN constructed can nicely fit the velocity profiles and can precisely predict the discharges for the conditions investigated. Copyright © 2005 John Wiley & Sons, Ltd.     

位场DFT算法研究

本文推广了经典的抽样定理,并据此导出了函数有限离散傅里叶变换误差方程（简称DFT误差方程,下同）。该方程把有限离散傅里叶变换中固有的离散效应和有限效应表示为确切的数学形式。离散效应被表示为一个含整参变量（参变量取0,1,…,N-1）的复无穷级数;有限效应被表示为一个含整参变量（参变量取0,1,…,N-1）的复无穷级数的DFT。 基于DFT误差方程和位函数特点,作者提出了两种位场数值傅里叶变换新算法--移样法和等效源续尾叠样法。移样法可近百倍地提高位场数值傅里叶反变换的精度,等效源续尾叠样法可数十倍地提高正变换精度。两种算法都不需要增加资料长度和取样密度,因而基本不需要增加计算机时间和内存。文中给出了算例。