高速铁路通用地面控制测量数据处理自动化系统研制

介绍了具有自主知识产权的高速铁路通用地面控制测量数据处理自动化系统软件（FSDI-GDPAS）的总体设计、功能模块设计及其涉及到的关键算法与相关理论,并通过具体工程实践说明软件的有效性和可靠性。     

Automated watershed subdivision for simulations using multi-objective optimization

A qualitative trial-and-error approach is commonly used to define watershed subdivisions through varying a single topographic threshold value. A methodology has been developed to quantitatively determine spatially variable threshold values using topography and a user-defined landscape reference layer. Optimization and topographic parameterization algorithms were integrated to create solutions that minimize the number of sub-watersheds and maximize the agreement between the discretized watershed and the reference layer. The system was evaluated using different reference datasets such as soil type, land management, and landscape form. Comparison of simulated results indicated that the scenario using land management as the reference layer yielded results closer to the scenario subdivided using a constant topographic threshold but with approximately 10 times more sub-catchments and therefore indicating customization of the watershed subdivision to the user-defined reference layer. The proposed optimization technology could be used in adequately applying watershed modeling technology in developing conservation practice implementation plans.     

Application of variational algorithms in semi- lagrangian framework

1.IntroductionWeatherforecastingmodelisasetofpartialdifferentialequations(PDE).Itshouldsatisfycertaininitial--boundaryconditions.Clearly,oneofthemostimportantimprovementsinweatherforecastingmodelistooptimizeitsinitialandboundaryconditions.Forthesimplicityofdiscussion,wemightregardthespatialboundaryconditionasakindofinitialconditioninspatialdimension.Aneffectivedataassimilationprocedureisrequiredinordertoutilizewidelycollectivedatafortheweatherforecastingmodelandfindanoptimalinitialcondition.…     

分形分析中的无标度区确定问题

分形无标度区的求取是随机分形应用研究的前提和基础。介绍目前求解无标度区的几种方法并分析其优缺点,提出一种基于标准偏差的自适应方法。同时针对自然地形、遥感图像等特大尺度范围的情况,在该方法中引入遗传算法,应用遗传算法的快速寻优功能,加快标度区间的确定速度。将这些方法应用于地形分析中的分形参数提取实验,证明自适应方法能较为准确、可靠地提取分形参数;而加入遗传算法的改进方法,大大地缩短了无标度区间的搜索时间,为大尺度范围分形对象的特征值快速测量提供有力的支持。     

基于遗传算法地震短期综合预报分类系统在天山地震带的应用

应用“基于遗传算法的地震预报分类系统”建立天山地震带8个区的地震短期综合预报模型。在前人研究基础上对此分类系统的应用方法做了以下改进：以半年或一年样本窗内的地震活动资料预报未来3个月最大地震;采用阈值划分异常,区分高值和低值异常两类参数,再用异常持续时间进行地震环境信息编码;在研究区内,根据一年和半年样本窗和震级错半级的分档形式,形成4种地震环境信息编码方式。计算机自动运行此系统程序,寻找各自的预报模型。对预留样本的检验按震级区间进行规则对应率、虚报率和地震对应率、漏报率的效能评价,结果表明南天山各区检验情况好于北天山;对北天山预测出5级以上、南天山6级以上地震以及能给出有效重叠震级区间的模型加权后认为南天山中西段、柯坪块体区检验情况较好。结果还表明半年样本窗检验效能普遍高于一年窗,对较低震级的检验情况一般要好于较高震级。     

基于ArcGIS Engine的飞机人工增雨航线自动化设计算法研究

人工增雨作为应急抗旱和缓解水资源紧张的重要手段,与社会经济可持续发展、生态安全和人民生活密切相关。航线设计是飞机人工增雨作业方案设计的一项重要内容,基于GIS平台自动化设计飞行航线将成为趋势。在传统飞行航线设计方案的基础上,研究提出了基于ArcGIS Engine的半圆弧过渡条播航线、＂弓＂字形条播航线和＂之＂字形条播航线三种层状云作业＂穿云＂航线与一种对流云或层积混合云作业＂绕云＂航线的自动化设计算法。应用结果显示,四种自动化算法均能够快速有效地设计出飞机航线,取得很好的效果。     

TSIP中期地震预报方法在辽宁地区的应用与研究

本文用ＣＮ算法研究了辽宁省两个地震重点监视防御区的中强震前的强震发生概率增长时间,结果表明预测效果较好,有震报准率为９０％,ＴＩＰ预测警戒占时空率为３０％左右,Ｒ值评分为０．６左右。在ＴＩＰ预测的基础上,进一步用ＳＩＰ方法分析这两个区域的空间背景发震概率的不均匀分布。综合应用ＴＩＰ方法和ＳＩＰ方法,对辽宁省及邻近地区进行了试验性地震预报。     

遗传算法及其在图像阈值选取中的应用

论述了遗传算法的基本原理、操作和特点,并以图像阈值选取中的最大类间方差法为例,给出用遗传算法优化图像阈值选取的步骤和方法,实验结果表明了这一方法的有效性。     

Pumping optimization of coastal aquifers based on evolutionary algorithms and surrogate modular neural network models

Pumping optimization of coastal aquifers involves complex numerical models. In problems with many decision variables, the computational burden for reaching the optimal solution can be excessive. Artificial Neural Networks (ANN) are flexible function approximators and have been used as surrogate models of complex numerical models in groundwater optimization. However, this approach is not practical in cases where the number of decision variables is large, because the required neural network structure can be very complex and difficult to train. The present study develops an optimization method based on modular neural networks, in which several small subnetwork modules, trained using a fast adaptive procedure, cooperate to solve a complex pumping optimization problem with many decision variables. The method utilizes the fact that salinity distribution in the aquifer, depends more on pumping from nearby wells rather than from distant ones. Each subnetwork predicts salinity in only one monitoring well, and is controlled by relatively few pumping wells falling within certain control distance from the monitoring well. While the initial control area is radial, its shape is adaptively improved using a Hermite interpolation procedure. The modular neural subnetworks are trained adaptively during optimization, and it is possible to retrain only the ones not performing well. As optimization progresses, the subnetworks are adapted to maximize performance near the current search space of the optimization algorithm. The modular neural subnetwork models are combined with an efficient optimization algorithm and are applied to a real coastal aquifer in the Greek island of Santorini. The numerical code SEAWAT was selected for solving the partial differential equations of flow and density dependent transport. The decision variables correspond to pumping rates from 34 wells. The modular subnetwork implementation resulted in significant reduction in CPU time and identified an even better solution than the original numerical model.     

Single‐and multi‐objective genetic algorithm optimization for identifying soil parameters

This paper discusses the quality of the procedure employed in identifying soil parameters by inverse analysis. This procedure includes a FEM‐simulation for which two constitutive models—a linear elastic perfectly plastic Mohr–Coulomb model and a strain‐hardening elasto‐plastic model—are successively considered. Two kinds of optimization algorithms have been used: a deterministic simplex method and a stochastic genetic method. The soil data come from the results of two pressuremeter tests, complemented by triaxial and resonant column testing. First, the inverse analysis has been performed separately on each pressuremeter test. The genetic method presents the advantage of providing a collection of satisfactory solutions, among which a geotechnical engineer has to choose the optimal one based on his scientific background and/or additional analyses based on further experimental test results. This advantage is enhanced when all the constitutive parameters sensitive to the considered problem have to be identified without restrictions in the search space. Second, the experimental values of the two pressuremeter tests have been processed simultaneously, so that the inverse analysis becomes a multi‐objective optimization problem. The genetic method allows the user to choose the most suitable parameter set according to the Pareto frontier and to guarantee the coherence between the tests. The sets of optimized parameters obtained from inverse analyses are then used to calculate the response of a spread footing, which is part of a predictive benchmark. The numerical results with respect to both the constitutive models and the inverse analysis procedure are discussed. Copyright © 2011 John Wiley & Sons, Ltd.