基于钢结构有限元软件的地铁隔断门门扇结构分析

地下铁道防护密隔断装装置应用于地下铁道，它能在战时把地下铁道空间隔断，并形成大型人防工程，具有明显的战备效益和经济效益，门扇是该装置中最重要的部件之一，应用钢结构有限元软件SAP91建立了地铁防护密闭隔断门门扇的结构模型，并对其进行有限元分析，通过门扇的应力分布及各点位移的结果确定门扇的结构，解决了该装置中直接受力件的结构和强度问题。     

Isomorphic pairs of homogeneous functions and their morphisms

Summary. In this paper we determine all iseomorphic pairs (isomorphic pairs with monotonic, thus continuous isomorphisms) of continuous, strictly increasing, linearly homogeneous functions defined on cartesian squares I ² and J ² of intervals of positive numbers or on their restrictions or and or We prove that, if the iseomorphy is nontrivial, then each homogeneous function is a (weighted) geometric or power mean or a joint pair of such means. In functional equations terminology this means that all nontrivial continuous strictly increasing linearly homogeneous solutions G, H (with the continuous strictly monotonic F also unknown) of the equation on D _< or D _> are weighted geometric or power means, while on I ² they are joint pairs of weighted geometric means or of weighted power means.     

The Rogalski–Cornet theorem and a Leontief-type input–output inclusion

In this paper, a Rogalski–Cornet-type surjectivity theorem without any continuity assumptions is proved. Some stability results for certain set-valued maps based on this result are also discussed. By applying these results to a generalized Leontief input–output inclusion problem, some solvability and stability criteria are obtained.     

Curve forecasting by functional autoregression

This paper deals with the prediction of curve-valued autoregression processes. It develops a novel technique, predictive factor decomposition, for the estimation of the autoregression operator. The technique is based on finding a reduced-rank approximation to the autoregression operator that minimizes the expected squared norm of the prediction error.Implementing this idea, we relate the operator approximation problem to the singular value decomposition of a combination of cross-covariance and covariance operators. We develop an estimation method based on regularization of the empirical counterpart of this singular value decomposition, prove its consistency and evaluate convergence rates.The method is illustrated by an example of the term structure of the Eurodollar futures rates. In the sample corresponding to the period of normal growth, the predictive factor technique outperforms the principal components method and performs on a par with custom-designed prediction methods.     

On the distribution tail of an integrated risk model: A numerical approach

We consider an insurance risk process with the possibility to invest the capital reserve into a portfolio consisting of a risky asset and a riskless asset. The stock price is modelled by an exponential Lévy process and the riskless interest rate is assumed to be constant. We aim at the risk assessment of the integrated risk process in terms of a high quantile or the far out distribution tail. We indicate an application to an optimal investment strategy of an insurer.     

On extremal solutions of inclusion problems with applications to game theory

A recursion principle, generalized iteration methods and the axiom of choice are applied to prove the existence of extremal fixed points of set-valued mappings in posets, extremal solutions of an inclusion problem, and extremal Nash equilibria for a normal-form game.     

Null sets and games in Banach spaces

The notion of Aronszajn-null sets generalizes the notion of Lebesgue measure zero in the Euclidean space to infinite dimensional Banach spaces. We present a game-theoretic approach to Aronszajn-null sets, establish its basic properties, and discuss some ensuing open problems.     

On reinsurance and investment for large insurance portfolios

We consider a problem of optimal reinsurance and investment for an insurance company whose surplus is governed by a linear diffusion. The company’s risk (and simultaneously its potential profit) is reduced through reinsurance, while in addition the company invests its surplus in a financial market. Our main goal is to find an optimal reinsurance-investment policy which minimizes the probability of ruin. More specifically, in this paper we consider the case of proportional reinsurance, and investment in a Black-Scholes market with one risk-free asset (bond, or bank account) and one risky asset (stock). We apply stochastic control theory to solve this problem. It transpires that the qualitative nature of the solution depends significantly on the interplay between the exogenous parameters and the constraints that we impose on the investment, such as the presence or absence of shortselling and/or borrowing. In each case we solve the corresponding Hamilton-Jacobi-Bellman equation and find a closed-form expression for the minimal ruin probability as well as the optimal reinsurance-investment policy.     

An evolutionary game based particle swarm optimization algorithm

Particle swarm optimization (PSO) is an evolutionary algorithm used extensively. This paper presented a new particle swarm optimizer based on evolutionary game (EGPSO). We map particles’ finding optimal solution in PSO algorithm to players’ pursuing maximum utility by choosing strategies in evolutionary games, using replicator dynamics to model the behavior of particles. And in order to overcome premature convergence a multi-start technique was introduced. Experimental results show that EGPSO can overcome premature convergence and has great performance of convergence property over traditional PSO.     

Solutions of two-factor models with variable interest rates

The focus of this work is on numerical solutions to two-factor option pricing partial differential equations with variable interest rates. Two interest rate models, the Vasicek model and the Cox–Ingersoll–Ross model (CIR), are considered. Emphasis is placed on the definition and implementation of boundary conditions for different portfolio models, and on appropriate truncation of the computational domain. An exact solution to the Vasicek model and an exact solution for the price of bonds convertible to stock at expiration under a stochastic interest rate are derived. The exact solutions are used to evaluate the accuracy of the numerical simulation schemes. For the numerical simulations the pricing solution is analyzed as the market completeness decreases from the ideal complete level to one with higher volatility of the interest rate and a slower mean-reverting environment. Simulations indicate that the CIR model yields more reasonable results than the Vasicek model in a less complete market.