一种新的地球物理反演方法——模拟原子跃迁反演法

详细研究了一般地球物理反问题的迭代优化求解过程与物理学中原子跃迁过程的对应关系,建立了反演问题中模型空间、初始模型、局部极值模型、最优化模型等与原子的态空间、定态、激发态、基态等的对应关系. 在此基础上,模拟了物理学中原子从激发态向基态跃迁的物理过程,建立了一种与原子跃迁过程相对应的非线性随机跃迁数学模型和模型解跃迁搜索准则,导出了适用于一般地球物理资料的模拟原子跃迁的非线性反演算法. 用理论测试函数对这种新的反演方法进行了数值试验,结果表明该方法具有解不依赖于初始模型、收敛速度快等优点.     

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.     

Fuzzy Optimization Neural Network Approach for Ice Forecast in the Inner Mongolia Reach of the Yellow River/Approche d'Optimisation Floue de Réseau de Neurones pour la Prévision de la Glace Dans le Tronçon de Mongolie Intérieure du Fleuve Jaune

Abstract

In ice forecasting, a key problem is the forecast of freeze-up and break-up dates. Ice-water mechanics and the principle of heat-exchange were mainly adopted in previous research. However, the mathematical models in these studies are complex and many parameters are required in relation to upstream and/or downstream gauging stations. Moreover, too many assumptions or simplifications for these parameters and constraints directly lead to low accuracy of the models and limitations as to their practical applications. This paper develops a fuzzy optimization neural network approach for the forecast of freeze-up date and break-up date. The Inner Mongolia reach lies in the top north of the Yellow River, China. Almost every year ice floods occur because of its special geographical location, hydrometeorological conditions and river course characteristics. Therefore, it is of particular importance for ice flood prevention to forecast freeze-up date and break-up date accurately. A case study in this region shows that the proposed methodology may allow obtaining useful results.     

基于梯度分析法的长江上游水库群供水-发电-环境互馈关系解析

长江上游水资源耦合系统优化调控涉及供水、发电和生态需水等相互竞争、不可公度的调控目标。其供水-发电-环境互馈协变机制难以数学解析和刻画，多维目标效益均衡优化调控难以实施。为此，以多目标优化、运筹学理论及方法为基础，提出了基于梯度分析法的供水-发电-环境两两互馈关系研究方法。通过多目标约束优化方法求解长江上游水库群联合优化调度在供水-发电-环境目标空间的最优解集，并进行插值构造了供水-发电-环境互馈关系多维空间曲面，以此为基础，采用一阶差分近似求解供水对环境和发电对环境偏导函数值，以量化环境对供水变化和发电变化响应的梯度，进而解析环境-供水和环境-发电间互馈协变关系。该方法为水库群优化调度多目标互馈关系研究提供了一种新的思路。     

蔚县矿区岩溶水供排结合研究

本文从系统观点出发,分析了矿区岩溶水供排结合的水文地质条件,提出了以供代排,合理的规划蔚县矿区地下水资源的供排结合方案。应用有限元数值模拟与最优化技术建立供排结合水量规划的教学模型,求出了蔚县矿区最佳水源地位置和最佳的供水开采量与疏干量,实现了较好的经济效益。     

An application of Karmarkar's interior-point linear programming algorithm for multi-reservoir operations optimization

Optimization of multi-reservoir systems operations is typically a very large scale optimization problem. The following are the three types of optimization problems solved using linear programming (LP): (i) deterministic optimization for multiple periods involving fine stage intervals, for example, from an hour to a week (ii) implicit stochastic optimization using multiple years of inflow data, and (iii) explicit stochastic optimization using probability distributions of inflow data. Until recently, the revised simplex method has been the most efficient solution method available for solving large scale LP problems. In this paper, we show that an implementation of the Karmarkar's interior-point LP algorithm with a newly developed stopping criterion solves optimization problems of large multi-reservoir operations more efficiently than the simplex method. For example, using a Micro VAX II minicomputer, a 40 year, monthly stage, two-reservoir system optimization problem is solved 7.8 times faster than the advanced simplex code in MINOS 5.0. The advantage of this method is expected to be greater as the size of the problem grows from two reservoirs to multiples of reservoirs. This paper presents the details of the implementation and testing and in addition, some other features of the Karmarkar's algorithm which makes it a valuable optimization tool are illuminated.     

黄河中下游地区旱涝分型及突变的初步分析

采用CEOF(复经验正交函数)对黄河中下游地区15个代表站点近500年来的旱涝等级指数分析结果表明,历史时期本地区的旱涝分布特点可用三种分布型表征:平均型、东西反相型和南北反相型,对上述三种旱涝分布型的时间振幅,应用Mann-Kendall方法进行突变检验,可以发现平均型和东西反相型近500年来发生旱涝突变,而南北反相型则相对比较稳定。     

REPRESENTATION OF SPECTRA BY CONTINUOUS FUNCTIONS

A general framework for manipulating spectra as functions in traditional multivariate methods such asPCA and PLS is described.The functional representation is very convenient for compression,ensuringsmoothness and continuity.There are two fundamentally different types of representations:(a)byfunctions and(b)by function coefficients.The use of coefficients is the most practical way of analysis.