Solving regularized least squares with qualitatively controlled adaptive cross‐approximated matrices

The adaptive cross‐approximation (ACA) technique is applied to accelerating an inverse‐problem solver that estimates charge distribution on a dielectric spacer. The ACA generates an approximated system‐matrix that enables us to carry out high‐speed inverse calculation. We designed an approximation procedure based on ACA with some additional concepts, that is, (a) partitioning of matrix based on algebraic information, (b) approximation quality control based on matrix norms, and so on. The tested solver (LSQR for regularized least squares) with ACA demonstrates about 10 times faster performance than that without ACA. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 159(3): 10–18, 2007; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20326     

台湾东北近海冬季上升流的数值模拟研究

该文利用已发展的三维斜压数值模式,模拟了冬季台湾东北近海上升流结构和空间分布。结果表明,冬季黑潮水在台湾东北海域向陆架入侵的同时,还伴随着强烈的上升流运动;从台湾北部的基隆近海经台湾东北角近海到宜兰海湾,存在3个上升流中心,量级为30~40×10-3cm s-1左右;在台湾东北近海最大上升流流速位于海底,约50×10-3cm s-1量级,并可直达海面。     

Inference for pth‐order random coefficient integer‐valued autoregressive processes

Abstract. A pth‐order random coefficient integer‐valued autoregressive [RCINAR(p)] model is proposed for count data. Stationarity and ergodicity properties are established. Maximum likelihood, conditional least squares, modified quasi‐likelihood and generalized method of moments are used to estimate the model parameters. Asymptotic properties of the estimators are derived. Simulation results on the comparison of the estimators are reported. The models are applied to two real data sets.     

土石坝无粘性粗粒料填筑标准和质量评价探讨

土石坝无粘性粗粒料填筑标准往往根据经验确定,而施工质量主要是通过碾压参数控制,理论依据不足。最大干密度和已建工程实践证明表面振动器法最大干密度与实际填筑干密度基本相等,可以直接指导设计和施工,据此提出了设计和施工控制标准;从砂砾石料、堆石料等无粘性粗粒料的特性探讨了填筑标准的适用范围,利用干密度与<5 mm粒径含量关系和填筑干密度,可以准确及时地对照填筑标准作出填筑质量评价结果。     

Effects of Process Conditions on Desalting and Demetalization of Crude Oil

The efficiency of desalting for six crude oils was studied with a SY-1 dynamic simulation experimental installation. The demulsifier DC2 was examined for 1#, 2#, and 4# crude oil and DC4 was used for 3#, 5#, and 6# crude oil. The effects of temperature, electric field gradient, dosage of demulsifier, and washing water on the desalting efficiency of six crude oils were investigated. The results showed that at the optimization process condition after desalting, the desalting efficiency and the salt content of 1# crude oil reached 89.17% and 1.92 mg/L; that of 2# crude oil reached 85.08% and 1.04 mg/L; that of 3# crude oil reached 91.06% and 1.35 mg/L; that of 4# crude oil reached 81.67% and 1.51 mg/L; that of 5# crude oil reached 81.03% and 2.32 mg/L; and that of 6# crude oil reached 86.64% and 2.67 mg/L. Different crude oils have different metal contents. Three assistants, ammonium nitrate (TJ1), nitric acid (TJ3), and polyamine carboxylate (TJ4), were used to improve the efficiencies of desalting and demetalization of six crude oils. TJ4 was more efficient in removing calcium and iron for 1# and 2# crude oil. TJ1 was more efficient in desalting and demetalizing 5# crude oil. The efficiencies for removal of calcium, iron, nickel, and vanadium respectively reached 99.89%, 98.33%, 20.58%, and 43.02%. TJ3 has better efficiency desalting and demetalizing for 6# crude oil. With the concentration of TJ3 increasing from 0 to 80 mg/L, the desalting efficiency increases from 31.22% to 73.54%, and the iron removal efficiency increases from 56.0% to 74.05%.     

2，6-萘二甲酸二甲酯在有机溶剂中溶解度的测定与关联

Solubility of dimethyl-2,6-naphthalene dicarboxylate in acetic acid, N,N-dimethylfonnamide, N,N-dimethyl acetamide, dimethyl sulphoxide, and N-methyl-2-ketopyrrolidine were determined using a dynamic method. The measured systems were correlated by UNIFAC group contribution method. A new main group （aromatic ester, ACCOO） was defined to express the activity coefficients of the aromatic ester. New interaction parameters of the ACCOO group were expressed as the first-order function of temperature and were determined from the experimental data. The calculated results for the new interaction parameters were satisfactory. The measured systems were also correlated with the Wilson and 2-h models, and the results were compared with those of the UNIFAC model.     

Restricted overlapping balancing domain decomposition methods and restricted coarse problems for the Helmholtz problem

Overlapping balancing domain decomposition methods and their combination with restricted additive Schwarz methods are proposed for the Helmholtz equation. These new methods also extend previous work on non-overlapping balancing domain decomposition methods toward simplifying their coarse problems and local solvers. They also extend restricted Schwarz methods, originally designed to overlapping domain decomposition and Dirichlet local solvers, to the case of non-overlapping domain decomposition and/or Neumann and Sommerfeld local solvers. Finally, we introduce coarse spaces based on partitions of unity and planes waves, and show how oblique projection coarse problems can be designed from restricted additive Schwarz methods. Numerical tests are presented.     

基于EDA虚拟实验室仿真精确度优化算法的研究

描述了一种减少仿真时所需计算次数的新技术,使得产品的优化可通过参数的变化来实现,并介绍一种改进SA的算法对获得的结果进行优化。     

Simulation of macroscopic material behavior for uniaxial fiber-matrix composites, using a DAE-approach

The macroscopic deformation behavior of a fiber-reinforced aluminum-boron composite is investigated. Different periodic and random arrangements of the microstructure are considered with macroscopic hardening behavior due to the evolution of plastic zones on the microscale being taken into account.

For the solution of the initial boundary value problem, a non-standard algorithm is applied. It consists of the direct solution of the whole set of equations, treating all variables as global quantities. Together with a higher order time integration method (BDF2), an automatic step size control is used in the FEM calculations.     

Genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons

In this paper, we propose and investigate a new category of neurofuzzy networks—fuzzy polynomial neural networks (FPNN) endowed with fuzzy set-based polynomial neurons (FSPNs) We develop a comprehensive design methodology involving mechanisms of genetic optimization, and genetic algorithms (GAs) in particular. The conventional FPNNs developed so far are based on the mechanisms of self-organization, fuzzy neurocomputing, and evolutionary optimization. The design of the network exploits the FSPNs as well as the extended group method of data handling (GMDH). Let us stress that in the previous development strategies some essential parameters of the networks (such as the number of input variables, the order of the polynomial, the number of membership functions, and a collection of the specific subset of input variables) being available within the network are provided by the designer in advance and kept fixed throughout the overall development process. This restriction may hamper a possibility of developing an optimal architecture of the model. The design proposed in this study addresses this issue. The augmented and genetically developed FPNN (gFPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional FPNNs. The GA-based design procedure being applied at each layer of the FPNN leads to the selection of the most suitable nodes (or FSPNs) available within the FPNN. In the sequel, two general optimization mechanisms are explored. First, the structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gFPNN is quantified through experimentation in which we use a number of modeling benchmarks—synthetic and experimental data being commonly used in fuzzy or neurofuzzy modeling. The obtained results demonstrate the superiority of the proposed networks over the models existing in the references.