due to the probabilistic nature and uncertainties of structural parameters, reliability-based optimization will enable engineers to account for the safety of the structures and allow for its decision making applicability. thus, reliability-based design will substitute deterministic rules of codes of practice. space structures are of those types that have an exceedingly high range of applicabili...

In this paper a simulation approach for defaultable yield curve is developed within the Heath et al. (1992) framework. The default event is modelled using the Cox process when the stochastic intensity represents the credit spread. The forward credit spread volatility function is affected by the entire credit spread term structure. Cox process properties and the Monte Carlo simulations technique...

A stochastic programming model of optical ber manufacturing is cre ated The purpose is to set the best ber manufacturing goals while accounting for the uncertainty primarily in the yield and secondly in the demand The model is solved for the case when the data follows a multivariate discrete distribution The model is also solved for the case when the distribution is approximated by a multivaria...

Mingchuan Zhang and Su-shing Chen Department of Computer Science University of North Carolina Charlotte, NC 28223 In this paper, we present some results of evidential reasoning m understanding multispectral images of remote sensing systems. The Dempster-Shafer approach of combination of evidences is pursued to yield contextual classification results, which are compared with previous results of ...

A pointed quasigroup is said to be semicentral if it is principally isotopic to a group via a permutation on one side and a group automorphism on the other. Convex combinations of permutation matrices given by the one-sided multiplications in a semicentral quasigroup then yield doubly stochastic transition matrices of finite Markov chains in which the entropic behaviour at any time is independe...

Motivated by developments in renewable energy and smart grids, we formulate a stylized mathematical model of a transport network with stochastic load fluctuations. Using an affine control rule, we explore the trade-off between the number of controllable resources in a lossy transport network and the performance gain they yield in terms of expected transportation losses. Our results are explicit...

We exploit nonlinearity in NbN superconducting stripline resonators, which originates from local thermal instability, for studying stochastic resonance. As the resonators are driven into instability, small amplitude modulation (AM) signals are amplified with the aid of injected white noise. Simulation results based on the equations of motion for the system yield a good agreement with the experi...

We analyze mean-variance-optimal dynamic hedging strategies in oil futures for oil producers and consumers. In a model for the oil spot and futures market with Gaussian convenience yield curves and a stochastic market price of risk, we find analytical solutions for the optimal trading strategies. An implementation of our strategies in an out-of-sample test on market data shows that the hedging ...

The bond portfolio management problem is formulated as a stochastic program based on interest rate scenarios. The coefficients of the resulting program are subject to errors of various kind. In this paper, we complement the theoretical stability results of [10] by simulation experiments. Adapting the approach of [16] to problems based on perturbed yield curves, we then provide bounds for the op...

For a decision rule whose decision region is suboptimal we show how to transform the decision statistic to recover optimal performance. The procedure simply amounts to transforming the decision statistic to yield a combined statistic/decision function which is optimal. The approach may be thought of as a generalization of the stochastic resonance phenomenon, which employs a random linear transf...