Optimizing the simultaneous management of blood pressure and cholesterol for type 2 diabetes patients

We present a Markov decision process (MDP) model to determine the optimal timing of blood pressure and cholesterol medications. We study the use of our model for a high-risk population of patients with type 2 diabetes; however, the model and methods we present are applicable to the general population. We compare the optimal policies based on our MDP to published guidelines for initiation of blood pressure and cholesterol medications over the course of a patient’s lifetime. We also present a bicriteria analysis that illustrates the trade off between quality-adjusted life years and costs of treatment.     

Extension to infinite dimensions of a stochastic second-order model associated with shape splines

Motivated by the development of a probabilistic model for growth of biological shapes in the context of large deformations by diffeomorphisms, we present a stochastic perturbation of the Hamiltonian equations of geodesics on shape spaces. We study the finite-dimensional case of groups of points for which we prove that the strong solutions of the stochastic system exist for all time. We extend the model to the space of parameterized curves and surfaces and we develop a convenient analytical setting to prove a strong convergence result from the finite-dimensional to the infinite-dimensional case. We then present some enhancements of the model.     

机器人与其连带的安全装置构成的系统解的半离散化

对机器人与其连带的安全装置构成的系统模型中的修复率μi,i=2,3,4,5用初等阶级函数进行逼近,给出了系统的半离散化模型,进一步为数值计算打下了理论基础.     

具有热储备的可修复平行系统解的半离散化

针对具有热储备的可修复平行系统模型中修复率U(X)用初等阶梯函数进行逼近,给出了系统的半离散化模型,进一步为数值计算打下了理论基础.     

A Verified Optimization Technique to Locate Chaotic Regions of Hénon Systems

We present a new verified optimization method to find regions for Hénon systems where the conditions of chaotic behaviour hold. The present paper provides a methodology to verify chaos for certain mappings and regions. We discuss first how to check the set theoretical conditions of a respective theorem in a reliable way by computer programs. Then we introduce optimization problems that provide a model to locate chaotic regions. We prove the correctness of the underlying checking algorithms and the optimization model. We have verified an earlier published chaotic region, and we also give new chaotic places located by the new technique.     

PDE-based signal quantization

We present a new method for signal restoration/quantization based on diffusion reaction model with memory term. We prove that the model is stable, with the existence and uniqueness results. We also propose a numerical approximation that we prove the convergence and present some experiments on noisy signals.     

Calibration of a multifactor model for the forward markets of several commodities

We propose a model for the evolution of forward prices of several commodities, which is an extension of the factor forward model in [1, 2], to a market where multiple commodities are traded. We calibrate this model in a market where forward contracts on multiple commodities are present, using historical forward prices. First, we calibrate separately the four coefficients of each individual commodity, using an approach based on quadratic variation/covariation of forward prices. Then, with the same technique, we pass to the estimation of the mutual correlation among the Brownian motions driving the different commodities. This calibration is compared to a calibration method used by practitioners, which uses rolling time series and requires a modification of the model, but turns out to be more accurate in practice, especially with a low frequency of observed transaction. We present efficient methods to perform the calibration with both methods, as well as the calibration of the intercommodity correlation matrix. Then we calibrate our model to WTI, ICE Brent and ICE Gasoil forward prices. Finally we present a method for estimating spot volatility from forward parameters, with an application to the WTI spot volatility.     

Anisotropic Brown-Resnick space-time processes: estimation and model assessment

Spatially isotropic max-stable processes have been used to model extreme spatial or space-time observations. One prominent model is the Brown-Resnick process, which has been successfully fitted to time series, spatial data and space-time data. This paper extends the process to possibly anisotropic spatial structures. For regular grid observations we prove strong consistency and asymptotic normality of pairwise maximum likelihood estimates for fixed and increasing spatial domain, when the number of observations in time tends to infinity. We also present a statistical test for isotropy versus anisotropy. We apply our test to precipitation data in Florida, and present some diagnostic tools for model assessment. Finally, we present a method to predict conditional probability fields and apply it to the data.     

A model of hysteresis with two inputs

We formulate and analyze a new model of vector hysteresis for the case of two-input signals. We prove the essential mathematical properties of this model and we present the solutions to two identification problems connected with our model.     

A note for tightening 0–1 models

We describe two approaches for 0–1 program model tightening that are based on the coefficient increasing and reduction methods proposed in Dietrich, Escudero and Chance (1993). We present some characterizations for the new formulations to be tighter than the original model. It can be shown that tighter models can be obtained even when applying any of both approaches to a redundant constraint; see Escudero and Muñoz (1998). We also present some situations where these approaches cannot be applied.     

基于ZigBee的工业控制网络模型

将无线传感器网络技术成功应用于工业自动化,建立了基于ZigBee的工业控制网络模型,并成功应用于生产线的工业控制中.     

Generalized interaction in multigravity

We consider a general approach to describing the interaction in multigravity models in a D-dimensional space-time. We present various possibilities for generalizing the invariant volume. We derive the most general form of the interaction potential, which becomes a Pauli-Fierz-type model in the bigravity case. Analyzing this model in detail in the (3+1)-expansion formalism and also requiring the absence of ghosts leads to this bigravity model being completely equivalent to the Pauli-Fierz model. We thus in a concrete example show that introducing an interaction between metrics is equivalent to introducing the graviton mass.     

价格和库存均影响需求、部分拖后供给的易变质品生产库存

考虑产品的需求率受库存和销售价格的影响,拖后供给因子与需求得到满足的实际等待时间有关,建立了易变质品生产库存模型,给出了寻求最优生产策略和销售价格的方法,并分析参数变化对于平均利润、销售价格和服务率的影响.     

A curved exponential family model for complex networks

Networks are being increasingly used to represent relational data. As the patterns of relations tends to be complex, many probabilistic models have been proposed to capture the structural properties of the process that generated the networks. Two features of network phenomena not captured by the simplest models is the variation in the number of relations individual entities have and the clustering of their relations. In this paper we present a statistical model within the curved exponential family class that can represent both arbitrary degree distributions and an average clustering coefficient. We present two tunable parameterizations of the model and give their interpretation. We also present a Markov Chain Monte Carlo (MCMC) algorithm that can be used to generate networks from this model.     

A Vasicek-Type Short Rate Model With Memory Effect

We introduce a Vasicek-type short rate model which has two additional parameters representing memory effect. This model presents better results in yield curve fitting than the classical Vasicek model. We derive closed-form expressions for the prices of bonds and bond options. Although the model is non-Markov, there exists an associated Markov process that allows one to apply usual numerical methods to the model. We derive analogs of an affine term structure and term structure equations for the model, and, using them, we present a numerical method to evaluate contingent claims.     

Parsimonious cluster systems

We introduce in this paper a new clustering structure, parsimonious cluster systems, which generalizes phylogenetic trees. We characterize it as the set of hypertrees stable under restriction and prove that this set is in bijection with a known dissimilarity model: chordal quasi-ultrametrics. We then present one possible way to graphically represent elements of this model.     

A stochastic multiscale model for electricity generation capacity expansion

Long-term planning for electric power systems, or capacity expansion, has traditionally been modeled using simplified models or heuristics to approximate the short-term dynamics. However, current trends such as increasing penetration of intermittent renewable generation and increased demand response requires a coupling of both the long and short term dynamics. We present an efficient method for coupling multiple temporal scales using the framework of singular perturbation theory for the control of Markov processes in continuous time. We show that the uncertainties that exist in many energy planning problems, in particular load demand uncertainty and uncertainties in generation availability, can be captured with a multiscale model. We then use a dimensionality reduction technique, which is valid if the scale separation present in the model is large enough, to derive a computationally tractable model. We show that both wind data and electricity demand data do exhibit sufficient scale separation. A numerical example using real data and a finite difference approximation of the Hamilton–Jacobi–Bellman equation is used to illustrate the proposed method. We compare the results of our approximate model with those of the exact model. We also show that the proposed approximation outperforms a commonly used heuristic used in capacity expansion models.     

Analysis and finite element approximation of a Ladyzhenskaya model for viscous flow in streamfunction form

In this paper we consider a model for the motion of incompressible viscous flows proposed by Ladyzhenskaya. The Ladyzhenskaya model is written in terms of the velocity and pressure while the studied model is written in terms of the streamfunction only. We derived the streamfunction equation of the Ladyzhenskaya model and present a weak formulation and show that this formulation is equivalent to the velocity–pressure formulation. We also present some existence and uniqueness results for the model. Finite element approximation procedures are presented. The discrete problem is proposed to be well posed and stable. Some error estimates are derived. We consider the 2D driven cavity flow problem and provide graphs which illustrate differences between the approximation procedure presented here and the approximation for the streamfunction form of the Navier–Stokes equations. Streamfunction contours are also displayed showing the main features of the flow.     

Multistage stochastic demand-side management for price-making major consumers of electricity in a co-optimized energy and reserve market

In this paper, we take an optimization-driven heuristic approach, motivated by dynamic programming, to solve a class of non-convex multistage stochastic optimization problems. We apply this to the problem of optimizing the timing of energy consumption for a large manufacturer who is a price-making major consumer of electricity. We introduce a mixed-integer program that co-optimizes consumption bids and interruptible load reserve offers, for such a major consumer over a finite time horizon. By utilizing Lagrangian methods, we decompose our model through approximately pricing the constraints that link the stages together. We construct look-up tables in the form of consumption-utility curves, and use these to determine optimal consumption levels. We also present heuristics, in order to tackle the non-convexities within our model, and improve the accuracy of our policies. In the second part of the paper, we present stochastic solution methods for our model in which, we reduce the size of the scenario tree by utilizing a tailor-made scenario clustering method. Furthermore, we report on a case study that implements our models for a major consumer in the (full) New Zealand Electricity Market and present numerical results.     

一类具有可修复储备部件的人-机系统解的半离散化

针对一个具有两个运行部件和一个储备部件,考虑系统通常故障的发生,且系统故障修复时间服从一般分布的人-机系统模型,对系统模型中修复率用初等阶梯函数进行逼近,给出了系统的半离散化模型,为进一步数值计算打下理论基础.