离散时多元风险模型的破产概率

本文研究了离散时多元风险模型的破产概率问题.利用经典大偏差的方法,获得了有限水平的破产概率,推广了离散时一元风险模型的相应结论.     

离散时多元风险模型的破产概率

本文研究了离散时多元风险模型的破产概率问题. 利用经典大偏差的方法, 获得了有限水平的破产概率, 推广了离散时一元风险模型的相应结论.     

离散的三项分布风险模型的渐近解

本文研究了离散的三项分布风险模型,在调节系数存在的前提下,借助于离散更新方程的一个极限定理,对于充分大的初始盈余给出了最终破产概率、破产前一刻的盈余和破产时赤字的概率的渐近解．其结果可以在离散的多项分布风险模型中得到推广．     

一类二元离散神经网络模型的渐近性

本文考虑的是一类具有分段常数非线性时滞差分系统,该系统可作为二元人工神经网络模型的离散形式,本文得到了系统解的渐近性的一些结果。     

离散线性投资组合模型的分枝定界算法

本文提出了一类新的带整数交易手数和凹型交易费用的均值绝对偏差模型(MAD)和极大极小投资组合模型(Minmax),并给出了离散模型的分枝定界算法.我们分别用随机产生的数据和Nasdaq股票市场的真实数据进行了数值实验,数值分析表明在一定的收益水平下均值绝对偏差离散模型风险控制上优于极大极小投资组合离散模型,而计算效率上极大极小投资组合离散模型优于期望绝对偏差离散模型.     

汽车保险的精算模型及其应用

本文应用我国一家保险公司的实际数据 ,对各种可以反映保单持有人索赔次数的模型 (包括负二项模型、泊松 -逆高斯模型、二元风险模型、三元风险模型、二项 -贝塔模型和负二项 -帆塔模型 )分别进行了拟合 ,结果表明三元风险模型拟合效果最好 ,因此利用三元风险模型构造了对保单持有人根据后验风险的大小调整其续期保费的系统     

离散的三项分布风险模型

本文探讨了离散的三项分布风险模型，重点研究了与风险有关的最终破产概率和破产前一刻的盈余的概率律．本文对任意的初始盈余u≥0，给出了上述概率或概率律的递推公式，变换公式和显式公式．其结果可以在离散的多项分布风险模型中得到推广．     

时标上的一类二元神经网络模型的渐进性

在基于时标的稳定性理论基础上,考虑了时标上的一类二元神经网络动力系统的收敛性的充分条件,所得结论统一了已有连续和离散形式.通过讨论时标上一类带有McCulloch-pitts型信号函数的二元神经网络模型的渐进行为.将动力模型转化为时标上的几个方程来考虑,并应用时标中的微分学理论以及基本的不等式放缩传递方法,通过对建立的一维映射的迭代规律进行分析,得到神经网络模型的收敛性.     

不完全信息下两个内部交易者的交易行为分析

当市场上存在两个拥有不完全信息的内部交易者时,研究了其对待风险的态度分别为风险喜好、风险中性与风险厌恶情况下模型在混合策略空间中离散时间的均衡解和高频交易下均衡的渐近行为特征,并分析了相关模型的经济金融学意义.     

基于净现值的离散型多项目多期投资优化模型

关于资本结构优化模型的讨论已经有了很好的结论,即基于项目组合的净现值最大化,对于多项目单期优化模型已经有了比较满意的结论.在已有结论的基础上研究了离散型多项目多期投资组合优化模型的一般形式,首先针对离散型多项目分期持续期相等的投资组合提出了一般优化模型,然后讨论离散型多项目分期持续期不全相等的投资组合优化模型,最后讨论了引进组合风险的投资组合优化模型。     

New perspectives in competitive location theory

This paper gives new perspectives in competitive location theory by considering new norms in two-dimensional problems and by considering (for the first time) the competitive location problem on a graph. The results in competitive location theory are generalized by exploiting an isomorphism to the literature in voting theory and by developing new results for competitive location problems on a graph.     

Optimal control for parabolic systems with competitive interactions

We consider a two-dimensional parabolic system with general competitive interactions as a two-player game with conflicting objectives and with controls on the inhomogencous (source) terms. We show the existence of an optimal solution of the game as the saddle point of a suitable objective functional.     

Smoothing noisy data for irregular regions using penalized bivariate splines on triangulations

The penalized spline method has been widely used for estimating univariate smooth functions based on noisy data. This paper studies its extension to the two-dimensional case. To accommodate the need of handling data distributed on irregular regions, we consider bivariate splines defined on triangulations. Penalty functions based on the second-order derivatives are employed to regularize the spline fit and generalized cross-validation is used to select the penalty parameters. A simulation study shows that the penalized bivariate spline method is competitive to some well-established two-dimensional smoothers. The method is also illustrated using a real dataset on Texas temperature.     

Examination of a new finite element method applied to convection heat transfer

A new finite element formulation for two-dimensional viscous flow and convection heat transfer is presented. The current method was designed in particular to be competitive with finite difference methods in terms of storage requirements, solution times, and range of applicability. Novel features of the formulation include the use of a streamline upwind approximation for the advection terms and an equal order velocity and pressure approximation.The current paper focuses on the features of the method which allow the formulation to be competitive with available finite difference methods. The method is illustrated by application to two examples including a natural convection example and a forced convection example.     

竞争型二元风险模型破产概率

本文研究了竞争型的二元风险模型,定义了两类破产概率以及状态过程,利用经典风险模型的已有结果和条件期望的性质,得到两类破产概率表达式,以及单个保险公司有限时间破产概率和最终破产概率,并给出两个保险公司的状态过程的概率分布列.     

Reducing network and computation complexities in neural based real-time scheduling scheme

Multiprocessor real-time scheduling is an important issue in many applications. A neural network provides a highly effective method to obtain good solutions for real-time scheduling problems. However, multiprocessor real-time scheduling problems include multiple variables; processor, process and time, and the neural networks have to be presented in three dimensions with these variables. Hence, the corresponding neural networks have more neurons, and synaptic weights, and thus associated network and computational complexities increase. Meanwhile, a neural network using the competitive scheme can provide a highly effective method with less network complexity. Therefore, in this study, a simplified two-dimensional Hopfield-type neural network using competitive rule is introduced for solving three-dimensional multiprocessor real-time scheduling problems. Restated, a two-dimensional network is proposed to lower the neural network dimensions and decrease the number of neurons and hence reduce the network complexity; an M-out-of-N competitive scheme is suggested to greatly reduce the computational complexity. Simulation results reveal that the proposed scheme imposed on the derived energy function with respect to process time and deadline constraints is an appropriate approach to solving these class scheduling problems. Moreover, the computational complexity of the proposed scheme is greatly lowered to O(N × T²).     

High-Dimensional Fused Lasso Regression Using Majorization–Minimization and Parallel Processing

In this article, we propose a majorization–minimization (MM) algorithm for high-dimensional fused lasso regression (FLR) suitable for parallelization using graphics processing units (GPUs). The MM algorithm is stable and flexible as it can solve the FLR problems with various types of design matrices and penalty structures within a few tens of iterations. We also show that the convergence of the proposed algorithm is guaranteed. We conduct numerical studies to compare our algorithm with other existing algorithms, demonstrating that the proposed MM algorithm is competitive in many settings including the two-dimensional FLR with arbitrary design matrices. The merit of GPU parallelization is also exhibited. Supplementary materials are available online.     

Fourth-order alternating direction implicit compact finite difference schemes for two-dimensional Schrödinger equations

In this paper, alternating direction implicit compact finite difference schemes are devised for the numerical solution of two-dimensional Schrödinger equations. The convergence rates of the present schemes are of order O(h⁴+τ²). Numerical experiments show that these schemes preserve the conservation laws of charge and energy and achieve the expected convergence rates. Representative simulations show that the proposed schemes are applicable to problems of engineering interest and competitive when compared to other existing procedures.     

A filter-and-fan approach to the 2D HP model of?the?protein folding problem

We examine a prominent and widely-studied model of the protein folding problem, the two-dimensional (2D) HP model, by means of a filter-and-fan (F&F) solution approach. Our method is designed to generate compound moves that explore the solution space in a dynamic and adaptive fashion. Computational results for standard sets of benchmark problems show that the F&F algorithm is highly competitive with the current leading algorithms, requiring only a single solution trial to obtain best known solutions to all problems tested, in contrast to a hundred or more trials required in the typical case to evaluate the performance of the best of the alternative methods.     

Deterministic and stochastic analysis of a delayed allelopathic phytoplankton model within fluctuating environment

In this paper, we consider a two-dimensional model for two competitive phytoplankton species where one species is toxic phytoplankton and other is non-toxic species. The logistic growth of both the species follows the Hutchinson type growth law. First, we briefly discuss basic dynamical properties of non-delayed and delayed model system within deterministic environment. Next we formulate the stochastic delay differential equation model system to study the effect of environmental driving forces on the dynamical behavior. We calculate population fluctuation intensity (variance) for both species by Fourier transform method. Numerical simulations are carried out to substantiate the analytical findings. Significant results of our analytical findings and their interpretations from ecological point of view are provided in concluding section.