VaR风险控制的银行资产负债管理优化模型

以资产组合收益率的波动为标准反映风险,在既定的组合收益率下,以组合风险最小为目标,以VaR风险收益率为约束,以法律、法规和经营管理约束为条件,建立了银行资产负债管理优化模型.本模型的特色与创新为以收益率最大损失的形式、而不是收益额的形式来反映VaR,使组合决策更为方便;运用资产负债管理比率建立约束条件,控制流动性风险;以VaR约束保证既定收益率选取的合理性,使资产配给的风险限定在银行的承受能力范围内.     

一种面向对象体系结构的度量模型

针对面向对象体系结构的软件系统缺乏有效度量方法的现状,通过行为、逻辑、构件和部署4个互为补充的模型,对面向对象的软件进行了架构分析,并确定了度量数据的采集集合.基于架构分析获得的原始系统数据,吸收快速原型与白盒、黑盒的基本原理,作者提出了一种适合面向确定对象系统的功能-结构-原型度量模型FCPMM(Function Configuration Prototype Metric Model).结合面向对象的基本准则与基本遗传算法,导出了该模型的循环收敛算法,从而可动态求解软件系统的最优状态.最后利用Matlab仿真实例,从度量参数适应度和最佳个体解码值两个方面验证了该算法的可行性.     

供水管网水质模型校核面临的问题及对策

为解决大规模供水管网系统水质模型校核的难题,分析经验校核与自动校核所面临的问题,提出遗传算法并行化、实测确定模型初始参数、模型参数的有效分组等相应的对策.从而减少模型校核的变量,提高遗传算法运行效率,有效缩短模型自动校核的寻优时间.     

扩充编码符号的EZW改进算法

为了提高EZW算法的性能,分析发现EZW算法主扫描编码对最高频子带中不重要系数的编码存在冗余,且当重要系数的所有子孙系数都是不重要系数时的编码存在冗余.据此提出了扩充编码符号的EZW改进算法,用最高频子带的坐标作为限制条件来减少不重要系数的编码冗余;通过扩充编码符号和赋予原始EZW算法的4个编码符号新的适用范围的方案来减小第二种编码冗余.实验结果表明,本文算法使峰值信噪比提高0.9～2.3dB,从而证实了本文改进算法的有效性.     

A recognition method of vibration parameter image based on improved immune negative selection algorithm for rotating machinery

To overcome the limitations of traditional monitoring methods, based on vibration parameter image of rotating machinery, this paper presents an abnormality online monitoring method suitable for rotating machinery using the negative selection mechanism of biology immune system. This method uses techniques of biology clone and learning mechanism to improve the negative selection algorithm to generate detectors possessing different monitoring radius, covers the abnormality space effectively, and avoids such problems as the low efficiency of generating detectors, etc. The result of an example applying the presented monitoring method shows that this method can solve the difficulty of obtaining fault samples preferably and extract the turbine state character effectively, it also can detect abnormality by causing various fault of the turbine and obtain the degree of abnormality accurately. The exact monitoring precision of abnormality indicates that this method is feasible and has better on-line quality, accuracy and robustness.     

Simulation and optimization of SOFC-BCHP system

As the prime motor of dispersed energy system, the high-temperature solid oxide fuel cells (SOFC) are high efficient with large heat recovery. This study presents a simulation of SOFC building-based cooling, heat and power (BCHP) system, which can meet basic requirements in power and heating (cooling) of the designated customers. The peak power load can be met by power grid, while the peak heating (cooling) load requirement can be met by backup equipments. In order to solve the economic dispatch problem of the energy system, a restricted nonlinear optimization model has been developed. The production costs can be minimized via both the equality constraints of customer’s heat and power demands, and other inequality constrains of equipments’ capacities. The sequential quadratic programming method has been used to search the solution. The study indicates that the model can be used to optimize the system’s capacities and run strategy. An office building case has been computed, and it is indicated that the model can be served in design and optimization of SOFC-BCHP system.     

Application of ACO algorithm in protein structure prediction

The hydrophobic-polar (HP) lattice model is an important simplified model for studying protein folding. In this paper, we present an improved ACO algorithm for the protein structure prediction. In the algorithm, the "lone"ethod is applied to deal with the infeasible structures, and the "oint mutation and reconstruction"ethod is applied in local search phase. The empirical results show that the presented method is feasible and effective to solve the problem of protein structure prediction, and notable improvements in CPU time are obtained.     

Effective prediction of DEA model by neural network

In this paper,a fast neural network model for the forecasting of effective points by DEA model is proposed,which is based on the SPDS training algorithm.The SPDS training algorithm overcomes the drawbacks of slow convergent speed and partially minimum result for BP algorithm.Its training speed is much faster and its forecasting precision is much better than those of BP algorithm.By numeric examples,it is showed that adopting the neural network model in the forecasting of effective points by DEA model is valid.     

一类广义集值强非线性混合拟变分不等式(英文)

引进一类广义集值强非线性混合拟变分不等式,并且用投影技巧证明了它解的存在性.推广了广义集值强非线性混合变分不等式的许多结论.     

基于网络的多卡加密系统调度模型

在分析L inux系统单卡加密系统的基础上,详细分析了影响单卡加密系统并行处理数据报文效率的原因,提出了一种能够改善报文处理效率的基于网络的多卡加密系统调度模型,讨论了多卡加密系统调度模型的特点,分析了该模型中各模块的功能.通过实例,比较了单卡和多卡加密系统在并行处理数据报文时的差异.结果表明,多卡加密系统调度模型是网络平台下的信息安全传输的一种优化方法.