A Frisch-Newton Algorithm for Sparse Quantile Regression

Recent experience has shown that interior-point methods using a log barrier approach are far superior to classical simplex methods for computing solutions to large parametric quantile regression problems. In many large empirical applications, the design matrix has a very sparse structure. A typical example is the classical fixed-effect model for panel data where the parametric dimension of the model can be quite large, but the number of non-zero elements is quite small. Adopting recent developments in sparse linear algebra we introduce a modified version of the Prisch-Newton algorithm for quantile regression described in Portnoy and Koenker~([28]). The new algorithm substantially reduces the storage (memory) requirements and increases computational speed. The modified algorithm also facilitates the development of nonparametric quantile regression methods. The pseudo design matrices employed in nonparametric quantile regression smoothing are inherently sparse in both the fidelity and roughness penalty components. Exploiting the sparse structure of these problems opens up a whole range of new possibilities for multivariate smoothing on large data sets via ANOVA-type decomposition and partial linear models.     

Little-Preemptive Scheduling on Unrelated Processors

We consider the preemptive scheduling of n independent jobs on m unrelated machines to minimize the makespan. Preemptive schedules with at most 2m–3 preemptions are built, which are optimal when the maximal job processing time is no more than the optimal schedule makespan. We further restrict the maximal job processing time and obtain optimal schedules with at most m–1 preemptions. This is better than the earlier known best bound of 4m ²–5m+2 on the total number of preemptions. Without the restriction on the maximal job processing time, our (2m–3)-preemptive schedules have a makespan which is no more than either of the following two magnitudes: (a) the maximum between the longest job processing time and the optimal preemptive makespan, and (b) the optimal nonpreemptive makespan. Our (m–1)-preemptive schedules might be at most twice worse than an optimal one.     

Heisenberg方程的保结构计算

出了Heishenberg方程的保等时交换关系-辛格式,为Heishenberg图景下计算量子系统(特别是时间相关外场中的原子)的时间演化提供了保结构的算法,用这种算法计算了一个非线性谐振子,结果显示保等时交换关系-辛格式对求解Heishenberg方程是精确和有效的.     

Algorithm for Scheduling Variable-Length Messages in WDM Networks

In this paper, we develop and analyze a simple algorithm for scheduling variable length messages in WDM networks with a passive star coupler. We base our schemes on a star topology with centralized control and use a scheduling algorithm similar to the process management in UNIX system. Every node and message have a scheduling priority associated with them. By comparing our algorithm with random select algorithm, we find that significant improvement in performance can be achieved with very little extra cost.     

Analysis of iterative methods for saddle point problems: a unified approach

In this paper two classes of iterative methods for saddle point problems are considered: inexact Uzawa algorithms and a class of methods with symmetric preconditioners. In both cases the iteration matrix can be transformed to a symmetric matrix by block diagonal matrices, a simple but essential observation which allows one to estimate the convergence rate of both classes by studying associated eigenvalue problems. The obtained estimates apply for a wider range of situations and are partially sharper than the known estimates in literature. A few numerical tests are given which confirm the sharpness of the estimates.

     

注水油田年综合含水率预测的数学模型

本文将改进的灰色GM（1，1）模型用于某油田年综合含水率的近期发展趋势研究。在平均相对误差达到最小准则下，研究了模型中的背景值参数A和边值修正项￡对模型预测精度的影响。在此基础上，采用线性规划方法估计模型中的参数，基于遗传算法求解最佳背景值参数A和最佳边值修正项ε，以确保在相应的模型检验准则下预测的误差达到最小。结果表明，用改进的灰色GM（1，1）模型预测近期注水油田的综合含水率，预测值与实际值相对误差很小，预测精度很高，可以得到非常满意的结果。进一步的研究发现，改进的灰色GM（1，1）模型虽然近期预测精度很高，但研究长期的发展趋势是行不通的，为此又研究探讨了长期发展趋势模型。     

Free Vibrations of Transversely Isotropic Hollow Cylinders

An asymptotic process for evaluating the frequencies of free axisymmetric vibrations of transversely isotropic hollow cylinders is proposed. This process is developed in detail for a cylinder with hinge-supported ends and free lateral surfaces. The approaches which make it possible to construct algorithms for identifying their natural frequencies within the given interval are tested on model problems. The results from the Kirchhoff-Love and Ambartsumyan theories are compared with those from the 3D elasticity theory. In the first term of an asymptotic expansion, two frequencies coinciding with those obtained using the applied shell theory are found and a countable set of frequencies absent in this theory is determined.     

Development and Evaluation of Decision-Making Model for Stock Markets

The paper introduces an intelligent decision-making model which is based on the application of artificial neural networks (ANN) and swarm intelligence technologies. The proposed model is used to generate one-step forward investment decisions for stock markets. The ANN are used to make the analysis of daily stock returns and to calculate one day forward decision for purchase of the stocks. Subsequently the Particle Swarm Optimization (PSO) algorithm is applied in order to select the “the best” ANN for the future investment decisions and to adapt the weights of other networks towards the weights of the best network. The experimental investigations were made considering different forms of decision-making model: different number of ANN, ANN inputs, sliding windows, and commission fees. The paper introduces the decision-making model, its evaluation results and discusses its application possibilities.     

The effect of increasing the excitation level of the sodium atom on the structure of the NaArn polyatomic exciplexes

In this work, the geometrical structures, the formation energies, and electronic states of the Na(ms)Ar_n polyatomic exciplexes with m = 3-6 and n = 2-5 are studied by using a quantum-classical method. The interaction potential between an electronically excited sodium atom and argon atoms are calculated by using a one-electron model involving electron-Ar and electron-Na⁺ pseudopotentials, in which the Hamiltonian is diagonalized at every optimization step in the Basin Hopping algorithm. The relationship between the position of the electronically excited levels and the cluster geometry is investigated as a function of the excitation level and of the spatial extension of the excited electron orbital. We show that the equilibrium structures of the ground state Na(3s)Ar_n and those of the electronically excited states Na(4s)Ar_n, Na(5s)Ar_n, and Na(6s)Ar_n are significantly different. As a result of the detailed examination of the relationships between the geometrical structure and density distribution of the Na valence electron of the Na^∗Ar_n with n = 2-5 polyatomic exciplexes, we can see that for the Na(4s)Ar_n polyatomic exciplexes, the two extreme geometries, neutral Na(3s)Ar_n and ionic Na⁺Ar_n compete. It appears that none of them is the actual one. For Na(5s)Ar_n and Na(6s)Ar_n the valence electron is very weakly bound to the ionic core and described by a more diffused orbital so that the geometry and the formation energies of this excited state called Rydberg states converge towards those of the ionic cores.