A New Technique for Ill-Conditioned Linear Systems

The technique we propose for solving ill-conditioned linear systems consists of two steps. First we compute the regularized solution on some values of the regularization parameter . Then we use these solutions either to extrapolate at =0 or to estimate the regularized solution with determined by the generalized cross validation or by the L-curve method.     

A Hierarchical Model for Control of Flexible Manufacturing Systems

Flexible Manufacturing Systems (FMSs) are usually composed of general purpose machines with automatic tool changing capability and integrated material handling. The complexity of FMSs requires sophisticated control. In this paper we present a four-level control hierarchy and outline computationally feasible control algorithms for each level. The top level is concerned with the choice of part types and volumes to be assigned to the FMS over the next several months. The second level plans daily or shift production. Production levels are set and tools are allocated to machines so as to minimize holding and shortage costs. Various FMS environments are presented. The third level determines process routes for each part type in order to minimize material handling. Additional tools are loaded on machines when possible to maximize alternate routeing. Routes are then assigned to parts to minimize workload assignment, and these are used by level four for actual routeing, sequencing and material handling path control. The level three model is formulated as a linear program, and heuristics are used for level four. An example is provided to illustrate the completeness of the decision hierarchy and the relationships between levels.     

过度投资与其制约因素的实证分析——以制造业上市公司为例

经理的机会主义引发企业过度投资行为。西方学者通过考察投资与现金流相关性,研究企业过度投资问题并找到相应经验证据。本文利用上市公司(2005会计年度)数据,研究制造业上市公司是否存在过度投资行为以及相关制约机制是否有效。结果表明:我国上市公司存在过度投资行为;经理持股、举借债务、大股东性质、现金股利是过度投资行为的有效制约机制;公司治理机制中的独立董事并未发挥作用。     

Toeplitz Preconditioners for Toeplitz Systems with Nonnegative Generating Functions

The preconditioned conjugate gradient method is employed tosolve Toeplitz systems T_nx = b where the generating functionsof the n-by-n Toeplitz matrices T_n are continuous nonnegativeperiodic functions defined in [–,]. The preconditionedC_n are band Toeplitz matrices with band-widths independent ofn. We prove that the spectra of C_n^-1T_n are uniformly boundedby constants independent of n. In particular, we show that thesolutions of T_nx = b can be obtained in O(nlogn) operations.     

Knapsack-based Algorithms for Designing Cellular Manufacturing Systems

In this paper, we use a 0–1 linear programming model for the machine assignment problem in cellular manufacturing. The formulated machine assignment problem considers many manufacturing factors such as machine utilization cost, cost of intercellular moves, part demand, and operating time capacity. The problem is shown to be NP-complete. Two designing algorithms are proposed to exploit the problem structure of the knapsack problem. Computational experience of the two algorithms is also reported.     

Soft Systems Models for Knowledge Elicitation and Representation

The paper contends that the conceptual modes used in Soft Systems Methodology have an unusual logical status. This enables them to be rendered in modal logic and used as a framework for knowledge elicitation and for the design of knowledge-based systems with learning capability.     

生成学习系统的混沌与设计

认知学习是一种高度复杂的非线性现象.试图依据生成学习理论和经验学习的思想,建构含有记忆效应的生成学习系统动力学模型,探讨认知学习过程的复杂现象和变化特征,揭示学习系统波动的内生机制和学生认知的混沌规律,并在此基础上提出基于学习混沌的教学系统设计模式,期望能促进学生认知结构的发展.     

A High-Quality Preconditioning Technique for Multi-Length-Scale Symmetric Positive Definite Linear Systems

We study preconditioning techniques used in conjunction with the conjugate gradient method for solving multi-length-scale symmetric positive definite linear systems originating from the quantum Monte Carlo simulation of electron interaction of correlated materials. Existing preconditioning techniques are not designed to be adaptive to varying numerical properties of the multi-length-scale systems. In this paper, we propose a hybrid incomplete Cholesky (HIC) preconditioner and demonstrate its adaptivity to the multi-length-scale systems. In addition, we propose an extension of the compressed sparse column with row access (CSCR) sparse matrix storage format to efficiently accommodate the data access pattern to compute the HIC preconditioner. We show that for moderately correlated materials, the HIC preconditioner achieves the optimal linear scaling of the simulation. The development of a linear-scaling preconditioner for strongly correlated materials remains an open topic.     

A Note about Parabolic Systems and Analytic Semigroups

We investigate the question whether certain parabolic systems in the sense of Petrovskii fulfill the resolvent estimate required for the generation of an analytic semigroup and apply the result to a problem concerning the diffusion of gases.     

On Bers Generating Functions for First Order Systems of Mathematical Physics

Considering one of the fundamental notions of Bers’ theory of pseudoanalytic functions the generating pair via an intertwining relation we introduce its generalization for biquaternionic equations corresponding to different first-order systems of mathematical physics with variable coefficients. We show that the knowledge of a generating set of solutions of a system allows one to obtain its different form analogous to the complex equation describing pseudoanalytic functions of the second kind and opens the way for new results and applications of pseudoanalytic function theory. As one of the examples the Maxwell system for an inhomogeneous medium is considered, and as one of the consequences of the introduced approach we find a relation between the time-dependent one-dimensional Maxwell system and hyperbolic pseudoanalytic functions and obtain an infinite system of solutions of the Maxwell system. Other considered examples are the system describing force-free magnetic fields and the Dirac system from relativistic quantum mechanics.     

Expressivism about Knowledge and the Value of Knowledge

The aim of the paper is to state a version of epistemic expressivism regarding knowledge, and to suggest how this expressivism about knowledge explains the value of knowledge. The paper considers how an account of the value of knowledge based on expressivism about knowledge responds to the Meno Problem, the Swamping Problem, and a variety of other questions that pertains to the value of knowledge, and the role of knowledge in our cognitive ecology.     

A Learning Algorithm for the Control of Continuous Action Set-Point Regulator Systems

The convergence properties for reinforcement learning approaches, such as temporal differences and Q-learning, have been established under moderate assumptions for discrete state and action spaces. In practice, however, many systems have either continuous action spaces or a large number of discrete elements. This paper presents an approximate dynamic programming approach to reinforcement learning for continuous action set-point regulator problems, which learns near-optimal control policies based on scalar performance measures. The continuous-action space (CAS) algorithm uses derivative-free line search methods to obtain the optimal action in the continuous space. The theoretical convergence properties of the algorithm are presented. Several heuristic stopping criteria are investigated and practical application is illustrated by two example problems—the inverted pendulum balancing problem and the power system stabilization problem.