黑河水库单薄山梁排水洞方案优选研究

黑河水库是解决西安市城市供水、农田灌溉及水力发电的大型水利水电工程。其左岸的单薄山梁既构成大坝坝肩岩体,蓄水后又成为一天然坝体。水库蓄水后的渗漏及渗透稳定性决定了水库能否安全高效的运行。黑河工程指挥部在防渗灌浆帷幕施工后,提出在帷幕下游增设单排排水洞。就此对排水洞方案进行了优选研究。     

SOIL SPATIAL ANALYSIS AND AGRICULTURAL LAND USE OPTIMIZATION BY USING GIS

This paper discusses the methods and process of Geographic Information System(GIS) applied in soil spatial analysis ,involving the collection of soil spatial data that GIS required ,spatial analysis method of soil nutrient,land use,slope and exposure of geography,crop yield and other factors,and also including acquiring soil spatial information and creating thematic map,and so on .Taking Hengjing Town in Wuxian County of Jiangsu Province as a case study and the maximum income as a principle,and applying the GIS methods and their interrelated models,we have calculated the most optimized agricultural land and the possible maximum income of Hengjing Town.According to the method,we can rationally regulate local agricultural production,and put forward some scenarios for optimizing agricultural structure of Hengjing Town .The paper puts forward an evaluation method of land adaptability based on soil spatial analysis,and offers some research clews to optimize agricultural land use constitutions.so the paper will be have important reference value for soil study.     

A linear road object matching method for conflation based on optimization and logistic regression

The purpose of object matching in conflation is to identify corresponding objects in different data sets that represent the same real-world entity. This article presents an improved linear object matching approach, named the optimization and iterative logistic regression matching (OILRM) method, which combines the optimization model and logistic regression model to obtain a better matching result by detecting incorrect matches and missed matches that are included in the result obtained from the optimization (Opt) method for object matching in conflation. The implementation of the proposed OILRM method was demonstrated in a comprehensive case study of Shanghai, China. The experimental results showed the following. (1) The Opt method can determine most of the optimal one-to-one matching pairs under the condition of minimizing the total distance of all matching pairs without setting empirical thresholds. However, the matching accuracy and recall need to be further improved. (2) The proposed OILRM method can detect incorrect matches and missed matches and resolve the issues of one-to-many and many-to-many matching relationships with a higher matching recall. (3) In the case where the source data sets become more complicated, the matching accuracy and recall based on the proposed OILRM method are much better than those based on the Opt method.     

THE VARIABILITY CHARACTERISTICS AND PREDICTION OF GUANGDONG POWER LOAD DURING 2002 - 2004

The variability characteristics of Guangdong daily power load from 2002 to 2004 and its connection to meteorological variables are analyzed with wavelet analysis and correlation analysis.Prediction equations are established using optimization subset regression. The results show that a linear increasing trend is very significant and seasonal change is obvious. The power load exhibits significant quasi-weekly (5 - 7 days) oscillation, quasi-by-weekly (10 - 20 days) oscillation and intraseasonal (30 - 60 days) oscillation. These oscillations are caused by atmospheric low frequency oscillation and public holidays. The variation of Guangdong daily power load is obviously in decrease on Sundays, shaping like a funnel during Chinese New Year in particular. The minimum is found at the first and second day and the power load gradually increases to normal level after the third day during the long vacation of Labor Day and National Day. Guangdong power load is the most sensitive to temperature, which is the main affecting factor, as in other areas in China. The power load also has relationship with other meteorological elements to some extent during different seasons. The maximum of power load in summer, minimum during Chinese New Year and variation during Labor Day and National Day are well fitted and predicted using the equation established by optimization subset regression and accounting for the effect of workdays and holidays.     

Advantages of the analytic element method for the solution of groundwater management problems

In the simulation‐optimization approach, a coupled optimization and groundwater flow/transport model is used to solve groundwater management problems. The efficiency of the numerical method, which is used to simulate the groundwater flow, is one the major reason to obtain the best solution for a management problem. This study was carried out to examine the advantages of the analytic element method (AEM) in the simulation‐optimization approach, for the solution of groundwater management problems. For this study, the AEM and finite difference method (FDM) based flow models were developed and coupled with the particle swarm optimization (PSO)‐based optimization model. Furthermore, the AEM‐PSO and FDM‐PSO models developed were applied in hypothetical as well as real field conditions to address groundwater management problems and the results were compared. For the real field situation, the models developed were applied to the Dore River basin in France to minimize the installation and operational cost of new pumping wells taking the location and discharge of the pumping wells as decision variables. The constraints of the problem were identified with the help of stakeholders and water authority officials. The AEM flow model was developed to facilitate the management model particularly when at each iteration, the optimization model calls for a simulation model to calculate the values of groundwater heads. The results show that, at some points, the AEM‐PSO model is efficient in identifying the optimal location of wells and consequently results in optimal costs, sometimes difficult when using the FDM. Copyright © 2011 John Wiley & Sons, Ltd.     

Dual state-parameter estimation of root zone soil moisture by optimal parameter estimation and extended Kalman filter data assimilation

With well-determined hydraulic parameters in a hydrologic model, a traditional data assimilation method (such as the Kalman filter and its extensions) can be used to retrieve root zone soil moisture under uncertain initial state variables (e.g., initial soil moisture content) and good simulated results can be achieved. However, when the key soil hydraulic parameters are incorrect, the error is non-Gaussian, as the Kalman filter will produce a persistent bias in its predictions. In this paper, we propose a method coupling optimal parameters and extended Kalman filter data assimilation (OP-EKF) by combining optimal parameter estimation, the extended Kalman filter (EKF) assimilation method, a particle swarm optimization (PSO) algorithm, and Richards’ equation. We examine the accuracy of estimating root zone soil moisture through the optimal parameters and extended Kalman filter data assimilation method by using observed in situ data at the Meiling experimental station, China. Results indicate that merely using EKF for assimilating surface soil moisture content to obtain soil moisture content in the root zone will produce a persistent bias between simulated and observed values. Using the OP-EKF assimilation method, estimates were clearly improved. If the soil profile is heterogeneous, soil moisture retrieval is accurate in the 0-50 cm soil profile and is inaccurate at 100 cm depth. Results indicate that the method is useful for retrieving root zone soil moisture over large areas and long timescales even when available soil moisture data are limited to the surface layer, and soil moisture content are uncertain and soil hydraulic parameters are incorrect.     

渭河盆地断裂活动速率的粒子群算法反演

渭河盆地是我国典型的断陷盆地,是中国大陆地裂缝活动、地面沉降活动最剧烈的地区之一.本文利用2004-2007年间的GPS数据,采用粒子群算法与位错理论模型相结合,对渭河盆地主要断裂的三维滑动速率进行了反演计算分析.结果表明:(1)断裂活动性质与地质测量方法获得的结果基本一致:除韩城—华县断裂以张裂为主外,渭河盆地主要断裂均以正倾滑为主,并具有走滑特征,呈张裂的运动趋势;(2)从滑动速率来看,秦岭北侧大断裂速率最大,可达4.5 mm/a.固关—宝鸡断裂活动最小,活动速率仅为1 mm/a左右;(3)在趋势上与现有的地质资料基本一致,以EW向断裂活动最强,NE方向较强,而NW方向较弱,并且分布上呈现南强北弱的特征.     

应用粒子群算法优化地位指数曲线模型参数研究

以优势高和地位指数的估测误差最小为目标函数,采用粒子群优化算法求解地位指数曲线模型的参数.结合实例与免疫算法比较,结果表明:粒子群优化算法求解的参数使模型的总体误差更小,精度更高,拟合效果更理想,更加科学合理,同时也提高了幼林的估算精度.研究的结果为森林经营中生长模型参数的求解以及相关研究提供了新的应用思路,也拓宽了粒子群优化算法在林业科学中的应用.     

基于改进粒子群算法的地震标量波方程反演

针对标准粒子群优化(PSO)算法存在易出现早熟而陷入局部最优以及进化后期收敛速度慢等缺陷,通过考虑粒子所处位置间相互作用,提出了一种改进的并行粒子群优化算法.由于引入粒子位置间的相互影响,减少了粒子搜索过程盲目性,因此能有效提高算法的收敛速度.数值试验表明,这种改进的粒子群算法适用于二维标量波方程的速度反演,且算法具有...     

利用模拟退火算法的村镇土地利用空间优化调控模型

提出了一种顾及土地利用监测评价结果的村镇土地利用调控模型。该模型整合空间单元划分、调控单元判别、空间配置于一体,运用模拟退火算法,实现了多目标控制下的空间优化调控。实例验证了此模型的合理性。