Computation of mean-semivariance efficient sets by the Critical Line Algorithm

The general mean-semivariance portfolio optimization problem seeks to determine the efficient frontier by solving a parametric non-quadratic programming problem. In this paper it is shown how to transform this problem into a general mean-variance optimization problem, hence the Critical Line Algorithm is applicable. This paper also discusses how to implement the critical line algorithm to save storage and reduce execution time.     

关于完备格上的T-型矩阵方程

利用完备格L上的无限分配t-模T,研究了T-型矩阵方程A TX TB=C的解,得到该方程有解的一个等价条件。同时,在有解时给出求该方程整个解集的一个算法。     

Computing invariants of algebraic groups in arbitrary characteristic

Let G be an affine algebraic group acting on an affine variety X. We present an algorithm for computing generators of the invariant ring KG[X] in the case where G is reductive. Furthermore, we address the case where G is connected and unipotent, so the invariant ring need not be finitely generated. For this case, we develop an algorithm which computes KG[X] in terms of a so-called colon-operation. From this, generators of KG[X] can be obtained in finite time if it is finitely generated. Under the additional hypothesis that K[X] is factorial, we present an algorithm that finds a quasi-affine variety whose coordinate ring is KG[X]. Along the way, we develop some techniques for dealing with nonfinitely generated algebras. In particular, we introduce the finite generation ideal.     

Positron emission particle tracking-Application and labelling techniques

The positron emission particle tracking (PEPT) technique has been widely used in science and engineering to obtain detailed information on the motion and flow fields of fluids or granular materials in multiphase systems, for example, fluids in rock cracks, chemical reactors and food processors; dynamic behaviour of granular materials in chemical reactors, granulators, mixers, dryers, rotating kilns and ball mills. The information obtained by the PEPT technique can be used to optimise the design, operational conditions for a wide range of industrial process systems, and to evaluate modelling work. The technique is based on tracking radioactively labelled particles (up to three particles) by detecting the pairs of back-to-back 511 ke V -γ-rays arising from annihilation of emitted positrons. It therefore involves a positron camera, location algorithms for calculating the tracer location and speed, and tracer labelling techniques. This paper will review the particle tracking technique from tracking algorithm, tracer labelling to their application.     

An algorithmic approach to the construction of homomorphisms induced by maps in homology

This paper is devoted to giving the theoretical background for an algorithm for computing homomorphisms induced by maps in homology. The principal idea is to insert the graph of a given continuous map into a graph of a multi-valued representable map . The multi-valued representable maps have well developed continuity properties and admit a finite coding that permits treating them by combinatorial methods. We provide the construction of the homomorphism induced by such that . The presented construction does not require subsequent barycentric subdivisions and simplicial approximations of . The main motivation for this paper comes from the project of computing the Conley Index for discrete dynamical systems.

     

A modified dodge algorithm for the parabolized Navier–Stokes equations and compressible duct flows

A revised version of Dodge's split-velocity method for numerical calculation of compressible duct flow has been developed. The revision incorporates balancing of mass flow rates on each marching step in order to maintain front-to-back continuity during the calculation. The (chequerboard) zebra algorithm is applied to solution of the three-dimensional continuity equation in conservative form. A second-order A-stable linear multistep method is employed in effecting a marching solution of the parabolized momentum equations. A chequerboard iteration is ued to solve the resulting implicit non-linear systems of finite-difference equations which govern stepwise transition. Qualitive agreement with analytical predictions and experimental results has been obtained for some flows with well-known solutions.     

An efficient simplicial algorithm for computing a zero of a convex union of smooth functions

We present an efficient simplicial algorithm for computing a zero of a point-to-set mapping that is formed by piecing together smooth functions. Such mappings arise in nonlinear programming and economic equilibrium problems. Our algorithm, under suitable regularity conditions on the problem, generates a sequence converging at least Q-superlinearly to a zero of the mapping. Asymptotically, it operates in a space of reduced dimension, analogous to an active set strategy in the optimization setting, but it switches active sets automatically. Results of computational experiments are given. Research of this author was supported by a Fellowship from the Rockeffeller Foundation. Research of this author was partially supported by a fellowhip from the John Simon Guggenheim Memorial Foundation and by National Science Foundation Grant ECS-7921279.     

Distributed asynchronous computation of fixed points

We present an algorithmic model for distributed computation of fixed points whereby several processors participate simultaneously in the calculations while exchanging information via communication links. We place essentially no assumptions on the ordering of computation and communication between processors thereby allowing for completely uncoordinated execution. We provide a general convergence theorem for algorithms of this type, and demonstrate its applicability to several classes of problems including the calculation of fixed points of contraction and monotone mappings arising in linear and nonlinear systems of equations, optimization problems, shortest path problems, and dynamic programming. This research was contacted at the M.I.T. Laboratory for Information and Decision Systems with partial support provided by the Defense Advanced Research Projects Agency under Grant No. ONR-N00014-75-C-1183.     

An ellipsoid algorithm for nonlinear programming

We investigate an ellipsoid algorithm for nonlinear programming. After describing the basic steps of the algorithm, we discuss its computer implementation and present a method for measuring computational efficiency. The computational results obtained from experimenting with the algorithm are discussed and the algorithm's performance is compared with that of a widely used commercial code. This research was supported in part by The National Science Foundation, Grant No. MCS78-02096.     

基于模糊径向基函数神经网络的模糊数据建模研究

提出将模糊径向基函数神经网络(FRBFN)用于模糊数据的建模,并提出融和圆锥模糊向量的聚类方法和模糊线性回归的学习算法。仿真研究表明．FRBFN及其算法在模糊数据建模方面有一定的优势。