SVD方法在场的定量预测中的应用     

张礼平  柯怡明  王康康 《热带气象学报》2004,20(4):383-390

经SVD分析,截取足够多的预报场和因子场时间系数,使其相互关系代表两场的大尺度联系,预报场时间系数与其奇异向量线性组合估计场能反映原场主要特征.利用最小二乘法得到数值上最接近原场的初值,借助最优化技术,确定合理的系数,建立预测公式,由因子场时间系数预测预报场时间系数,同时订正预报场时间系数a1,a2,……,aN本身的误差和反演过程中分析误差造成的场格点趋势预测的误差.最后将预测的预报场时间系数和对应奇异向量反演为整个场的预报.预报过程重点考虑可预报的大尺度变化,滤去不可预报的小扰动,依据两场主要耦合关系,预测预报场未来的主要变化.  相似文献   

Estimating forest biomass using small footprint LiDAR data: An individual tree-based approach that incorporates training data   总被引：1，自引：0，他引：1  

Zachary J. Bortolot  Randolph H. Wynne   《ISPRS Journal of Photogrammetry and Remote Sensing》2005,59(6):824

A new individual tree-based algorithm for determining forest biomass using small footprint LiDAR data was developed and tested. This algorithm combines computer vision and optimization techniques to become the first training data-based algorithm specifically designed for processing forest LiDAR data. The computer vision portion of the algorithm uses generic properties of trees in small footprint LiDAR canopy height models (CHMs) to locate trees and find their crown boundaries and heights. The ways in which these generic properties are used for a specific scene and image type is dependent on 11 parameters, nine of which are set using training data and the Nelder–Mead simplex optimization procedure. Training data consist of small sections of the LiDAR data and corresponding ground data. After training, the biomass present in areas without ground measurements is determined by developing a regression equation between properties derived from the LiDAR data of the training stands and biomass, and then applying the equation to the new areas. A first test of this technique was performed using 25 plots (radius = 15 m) in a loblolly pine plantation in central Virginia, USA (37.42N, 78.68W) that was not intensively managed, together with corresponding data from a LiDAR canopy height model (resolution = 0.5 m). Results show correlations (r) between actual and predicted aboveground biomass ranging between 0.59 and 0.82, and RMSEs between 13.6 and 140.4 t/ha depending on the selection of training and testing plots, and the minimum diameter at breast height (7 or 10 cm) of trees included in the biomass estimate. Correlations between LiDAR-derived plot density estimates were low (0.22 ≤ r ≤ 0.56) but generally significant (at a 95% confidence level in most cases, based on a one tailed test), suggesting that the program is able to properly identify trees. Based on the results it is concluded that the validation of the first training data-based algorithm for determining forest biomass using small footprint LiDAR data was a success, and future refinement and testing are merited.  相似文献   

Numerical tools for geoscience computations: Semiautomatic differentiation—SD     

Abdulwahab A. Abokhodair 《Computational Geosciences》2007,11(4):283-296

This paper presents a differentiation method [referred to here as semiautomatic differentiation (SD)] based on generalization and extension of the Squire and Trapp formula for complex differentiation of real-valued functions. The performance of the generalized formulas for first-order derivatives is tested and compared with manual, automatic (AD), and finite difference (FD) techniques. My results show that, in terms of accuracy, the SD technique is competitive with AD, and in terms of implementation simplicity, it is identical to the FD method with the added advantage of being step-size insensitive and, hence, free from the step-size dilemma that plagues FD. Using central differencing in the complex plane, I extend the SD method to second-order derivatives, thus enabling approximation of the Hessians. Performance of the extension formulas is evaluated and compared with AD and FD methods. The results indicate that the differencing operation reduces the accuracy of the extension formulas by four to five orders of magnitude below that of the original Squire and Trapp formula. Nonetheless, compared to FD schemes, the SD method is six to seven orders of magnitude more accurate in all tests conducted. In addition, the extension formulas exhibit step-size (h) insensitive behavior over the entire h-range of the tests (1–10⁻³⁰), indicating high numerical stability of the schemes. I show by examples that SD provides a complete differentiation system that is computationally stable, efficient, highly accurate, and easy to implement.  相似文献   

Risk minimization in water quality control problems of a river system     

Subimal Ghosh  P.P. Mujumdar 《Advances in water resources》2006

Methodologies are presented for minimization of risk in a river water quality management problem. A risk minimization model is developed to minimize the risk of low water quality along a river in the face of conflict among various stake holders. The model consists of three parts: a water quality simulation model, a risk evaluation model with uncertainty analysis and an optimization model. Sensitivity analysis, First Order Reliability Analysis (FORA) and Monte–Carlo simulations are performed to evaluate the fuzzy risk of low water quality. Fuzzy multiobjective programming is used to formulate the multiobjective model. Probabilistic Global Search Laussane (PGSL), a global search algorithm developed recently, is used for solving the resulting non-linear optimization problem. The algorithm is based on the assumption that better sets of points are more likely to be found in the neighborhood of good sets of points, therefore intensifying the search in the regions that contain good solutions. Another model is developed for risk minimization, which deals with only the moments of the generated probability density functions of the water quality indicators. Suitable skewness values of water quality indicators, which lead to low fuzzy risk are identified. Results of the models are compared with the results of a deterministic fuzzy waste load allocation model (FWLAM), when methodologies are applied to the case study of Tunga–Bhadra river system in southern India, with a steady state BOD–DO model. The fractional removal levels resulting from the risk minimization model are slightly higher, but result in a significant reduction in risk of low water quality.  相似文献   

Designing an optimal multivariate geostatistical groundwater quality monitoring network using factorial kriging and genetic algorithms   总被引：1，自引：0，他引：1  

Ming-Sheng Yeh  Yu-Pin Lin  Liang-Cheng Chang 《Environmental Geology》2006,50(1):101-121

The optimal selection of monitoring wells is a major task in designing an information-effective groundwater quality monitoring network which can provide sufficient and not redundant information of monitoring variables for delineating spatial distribution or variations of monitoring variables. This study develops a design approach for an optimal multivariate geostatistical groundwater quality network by proposing a network system to identify groundwater quality spatial variations by using factorial kriging with genetic algorithm. The proposed approach is applied in designing a groundwater quality monitoring network for nine variables (EC, TDS, Cl⁻, Na, Ca, Mg, SO ₄ ²⁻ , Mn and Fe) in the Pingtung Plain in Taiwan. The spatial structure results show that the variograms and cross-variograms of the nine variables can be modeled in two spatial structures: a Gaussian model with ranges 28.5 km and a spherical model with 40 km for short and long spatial scale variations, respectively. Moreover, the nine variables can be grouped into two major components for both short and long scales. The proposed optimal monitoring design model successfully obtains different optimal network systems for delineating spatial variations of the nine groundwater quality variables by using 20, 25 and 30 monitoring wells in both short scale (28.5 km) and long scale (40 km). Finally, the study confirms that the proposed model can design an optimal groundwater monitoring network that not only considers multiple groundwater quality variables but also monitors variations of monitoring variables at various spatial scales in the study area.  相似文献   

Development of a framework of automated water quality parameter optimization and its application   总被引：1，自引：0，他引：1  

Kyung-Sub Kim  Chung-Hwan Je 《Environmental Geology》2006,49(3):405-412

This paper presents a methodology and framework for the development of an automated least-squares optimization tool for calibrating water quality parameters in QUAL2E. The method has been applied to estimate the optimal water quality parameters in simulation of stream water quality for the Anyang stream in Korea. The Monte Carlo analysis is used to assess the relative importance of model parameters for water quality constituents. It is found that μ_max and ρ are the most influential parameters for Chlorophyll-a modeling and K ₁ and K ₃ are critical parameters for variation of DO and BOD in the Anyang stream. A computer program for automated parameter calibration has been developed using a nonlinear GRG optimization algorithm. The application framework provides an intuitive and easy-to-use interface and allows visual evaluation of results. According to the simulation results, the automated approach is computationally efficient for evaluation of model parameters and converges on a best fit more rapidly and reliably than a trial and error method. The methodology proposed herein can be extended to other models to obtain the best possible parameter values.  相似文献   

Adsorption of BTEX on Surfactant Modified Granulated Natural Zeolite Nanoparticles: Parameters Optimizing by Applying Taguchi Experimental Design Method     

Laleh Seifi  Ali Torabian  Hossein Kazemian  Gholamreza Nabi Bidhendi  Ali Akbar Azimi  Shapoor Nazmara  Mohammad AliMohammadi 《洁净——土壤、空气、水》2011,39(10):939-948

In this paper, a novel adsorbent developed by means of granulating of natural zeolite nanoparticles (i.e., clinoptilolite) was evaluated for possible removal of the petroleum monoaromatics (i.e., benzene, toluene, ethylbenzene, and xylene, BTEX). To do this, the natural zeolite was ground to produce nanosized particulate, then modified by two cationic surfactants and granulated. The effect of various parameters including temperature, initial pH of the solution, total dissolved solids (TDS), and concentration of a competitive substance (i.e., methyl tert‐butyl ether, MTBE) were studied and optimized using a Taguchi statistical approach. The results ascertained that initial pH of the solution was the most effective parameter. However, the low pH (acidic) was favorable for BTEX adsorption onto the developed adsorbents. In this study, the experimental parameters were optimized and the best adsorption condition by determination of effective factors was chosen. Based on the S/N ratio, the optimized conditions for BTEX removal were temperature of 40°C, initial pH of 3, TDS of 0 mg/L, and MTBE concentration of 100 µg/L. At the optimized conditions, the uptake of each BTEX compounds reached to more than 1.5 mg/g of adsorbents.  相似文献   

Long-term regional hurricane hazard analysis for wind and storm surge   总被引：2，自引：0，他引：2  

Pruttipong Apivatanagul  Rachel Davidson  Brian Blanton  Linda Nozick 《Coastal Engineering》2011

This paper introduces a new method to estimate the long-term regional hurricane wind and storm surge hazard. The output is a relatively small set of hurricane scenarios that together represent the regional hazard. For each scenario, the method produces a hazard-consistent annual occurrence probability, and wind speeds and surge levels throughout the study area. These scenarios can be used for subsequent evacuation or loss estimation modeling. This optimization-based probabilistic scenario (OPS) method involves first simulating tens of thousands of candidate hurricane scenarios with wind speeds and approximate surge depths. A mixed-integer linear optimization is then used to select a subset of scenarios and assign hazard-consistent annual occurrence probabilities to each. Finally, a surge model is used to estimate accurate surge depths for the reduced set of events. The method considers the correlation between winds and surge depths and the spatial correlations of each; it is computationally efficient; and it makes explicit the tradeoff between the number of scenarios selected and the errors introduced by using a reduced set of events. A case study for Eastern North Carolina is presented in which a final set of 97 hurricanes provides unbiased results with errors small enough for many practical uses.  相似文献   

小生境遗传算法求解多峰问题在反演中应用   总被引：3，自引：3，他引：3  

杨慧珠  张世俊  杜祥 《地球物理学进展》2001,16(2):35-41

基于反演问题的不确定性和目标函数的多峰性，引入改进的小生境遗传算法，求解出目标函数的若干个局部峰（或全局峰），然后利用先验知识，判定得到满意解，并利用褶积模型进行层速度反演，通过理论速度与反演速度的比较，验证了进行多峰优化的有效性。  相似文献   

桁架结构基于地震可靠性分析的优化方法     

李鸿晶  冯启民 《地震工程与工程振动》1997,17(1):9-13

本文把桁架结构地震可靠性分析和最优化设计方法结合起来，以结构的地震失效率概率为目标函数，给出一种考虑地震可靠性的桁架结构的优化方法。该方法能够解决线性桁架体系在平稳的随机地震地面运动激励下的优化问题，并在给定投资的条件下设计出了安全可靠的桁架结构。  相似文献