一阶脉冲周期边值问题正解的存在性

通过引入一个新的锥,利用不动点指数相关理论,研究了一类一阶脉冲周期边值问题,讨论了其正解的存在性.     

Banach空间非线性脉冲Volterra型积分方程和积分-微分方程的可解性

本文在较宽松的条件下,研究了Banach空间非线性脉冲Volterra型积分方 程和脉冲积分一微分方程解的存在性,建立了新的存在性定理,本质上改进了某些已 知的结果.     

具有马尔科夫切换的随机脉冲时滞系统的均方指数稳定性（英文）

针对一类具有马尔科夫切换的随机脉冲时滞系统,考虑了均方指数稳定性问题.通过构造新的时变Lyapunov函数,得到了一类新的保证系统均方指数稳定性的条件,并且证明了所得到的条件不仅依赖于脉冲间隔的上界,还依赖于它的下界.和已有的参考文献相比,文章获得的结果具有较低的保守性.最后,利用数值仿真验证了所提方法的有效性.     

Banach空间无界域上二阶脉冲积分微分方程的解

在比较宽松的条件下，研究了Banach空间中二阶脉冲积分微分方程在正半实轴上具有无穷个脉冲点的初值问题的解的存在性。利用递归法、Tonelii序列和局部凸拓扑，建立了新的存在性定理，对郭大钧的结果做了本质改进。     

具脉冲扰动和时滞效应的拟线性抛物系统的(强)振动分析北大核心CSCD

研究一类具脉冲扰动和时滞效应的拟线性抛物系统的(强)振动性问题,利用新的处理拟线性扩散项的技巧和脉冲时滞微分不等式,建立了该类系统在Neumann边值条件下所有解(强)振动的若干新的充分条件.所得结果充分表明系统振动是由脉冲扰动和时滞效应引起的.     

一类具有时滞的中立型分数阶脉冲微分方程解的存在唯一性

基于分数阶脉冲微分方程解的新的积分形式,利用Banach不动点定理和Schauder不动点定理研究了在脉冲条件下一类具有时滞的中立型分数阶微分方程的柯西问题,得出了这类微分方程解的存在性和唯一性.     

具脉冲扰动和时滞效应的拟线性抛物系统的(强)振动分析

研究一类具脉冲扰动和时滞效应的拟线性抛物系统的(强)振动性问题,利用新的处理拟线性扩散项的技巧和脉冲时滞微分不等式,建立了该类系统在Neumann边值条件下所有解(强)振动的若干新的充分条件.所得结果充分表明系统振动是由脉冲扰动和时滞效应引起的.     

一类灰色脉冲随机时滞系统的几乎必然指数鲁棒稳定性

为了研究一类灰色脉冲随机时滞系统几乎必然指数稳定性的问题,首先利用Razumikhin方法和Lyapunov函数,给出了脉冲随机泛函微分系统几乎必然指数稳定的条件,然后基于此条件和时变灰矩阵的连续矩阵覆盖的分解技术,得到了该类灰色脉冲随机时滞系统几乎必然指数稳鲁棒定性的判据,最后通过一个数值例子说明了得判据是有效的和实用的.     

一类含有脉冲免疫和治疗的SIR流行病的分析

在考虑脉冲接种和脉冲治疗的基础上,本文提出了一类新的含有两个脉冲过程和治疗的SIR传染病模型.利用频闪映射和Floquet理论,研究了无病周期解的存在性与稳定性,这意味着疫情最终可能灭绝.此外,研究了该流行病持久流行的条件,获得了决定疫情是否发生的基本再生数.最后,通过数值模拟分析,说明了脉冲接种和脉冲治疗对疾病控制的影响.     

具非线性扩散项的脉冲抛物方程的强迫振动性

研究一类具非线性扩散项的脉冲抛物型方程解的强迫振动性问题,借助平均技巧和脉冲微分不等式,建立了该类方程在Dirichlet边值条件下所有解强迫振动的若干新的充分判据.结论充分表明振动是由脉冲效应引起的.     

A new multivariable grey prediction model with structure compatibility

A new multivariable grey prediction model was proposed by adding a dependent variable lag term, a linear correction term and a random disturbance term to the traditional GM(1,N) model. It was theoretically proved that the new model can be completely compatible with the mainstream single variable and multivariable grey prediction models by adjusting and changing the model's parameters. To test the performance of the new model, three case studies were performed. The simulation and prediction results of the new model were compared with those of other grey prediction models. Results showed that the new model had evidently superior performance to other grey models, which confirms that the structure design of the new model is more reasonable than those of the other existing grey prediction models.     

关于《中国城镇新增用地供给量的预测及其修正方法》的新模型建立及其比较

本文对文献［１］中的数据重新以时间序列为变量建立回归模型,通过比较新老模型的检验效果,显示新模型的优良性．又结合新模型重新给出了更为合理的新增用地控制方法     

基于JGLM-RM模型的动态稳健设计及其应用

根据动态稳健设计的基本思想和方法,结合联合广义线性模型(Joint Generalized linearmodel)和响应模型(Response model)各自的特点和优势,构建出基于JGLM-RM的动态稳健设计模型。利用新模型对具体工业案例进行了实证研究,结果表明新模型不仅能有效地区分具体噪声因子和潜在噪声因子对整个过程波动的影响,而且能够灵活地调节模型的截距和斜率。此外,新模型引入了均值和散度的联合广义线性模型因此能适应广泛的响应类型。     

程度下近似算子与变精度上近似算子的差运算模型

目的是探讨精度与程度的复合,建立并研究新的粗糙集拓展模型.基于程度与精度的逻辑差需求,提出了程度下近似算子与变精度上近似算子的差运算模型,得到了程度下近似算子与变精度上近似算子的差运算的宏观本质、精确描述与基本性质.并用一个医疗实例说明了模型的意义和应用.程度下近似算子与变精度上近似算子的差运算模型,部分的拓展了程度粗糙集模型和经典粗糙集模型.     

基于改进BP神经网络的电力负荷预测

在现有文献研究的基础上,对BP神经网络进行了深入研究,提出了一种新的LAFBP模型,给出了模型的标准BP算法、改进BP算法、权值和阈值的初始化方法.在此基础上,用新的LAFBP模型与传统的标准BP模型对黑龙江省巴彦县的电力负荷进行了预测.预测结果表明,新的LAFBP模型不仅克服了传统的BP模型外推效果不好的缺点,而且在模型的拟合精度、学习时间和学习次数方面明显优于传统的BP模型.     

光滑树图期权定价模型的叉熵分析法

为了克服CRR模型收敛的波动性,以及强调历史信息的预测作用的情况,提出了一个新奇的光滑收敛的树图模型.新模型基于历史信息,运用最小叉熵原理
来推导树图的关键参数p,u,d, 然后使用倒推法推断期权的价格.显然,新模型所得的期权的价格隐含着历史信息.由于最小叉熵原理是一个凸规划问题,能求得唯一的最优解,所以,新模型也适用于不完全金融市场期权定价.最后,数值算例表明,相比于CRR模型,新模型收敛光滑平稳且有更高的计算精度;对上涨(下跌)的二元期权、欧式期权,新模型都能光滑收敛于B-S公式.     

Permutation-induced acyclic networks for the job shop scheduling problem

In the literature of the combinatorial optimization problems, it is a commonplace to find more than one mathematical model for the same problem. The significance of a model may be measured in terms of the efficiency of the solution algorithms that can be built upon it. The purpose of this article is to present a new network model for the well known combinatorial optimization problem – the job shop scheduling problem. The new network model has similar structure as the disjunctive graph model except that it uses permutations of jobs as decision variables instead of the binary decision variables associated with the disjunctive arcs. To assess the significance of the new model, the performances of exact branch-and-bound algorithmic implementations that are based on both the new model and the disjunctive graph model are compared.     

A NEW DERIVATIVE FREE OPTIMIZATION METHOD BASED ON CONIC INTERPOLATION MODEL

In this paper, a new derivative free trust region method is developed basedon the conic interpolation model for the unconstrained optimization. The conic inter-polation model is built by means of the quadratic model function, the collinear scalingformula, quadratic approximation and interpolation. All the parameters in this model axedetermined by objective function interpolation condition. A new derivative free method isdeveloped based upon this model and the global convergence of this new method is provedwithout any information on gradient.     

Simultaneous variable selection for heteroscedastic regression models

In this paper, we propose a new criterion, named PICa, to simultaneously select explanatory variables in the mean model and variance model in heteroscedastic linear models based on the model structure. We show that the new criterion can select the true mean model and a correct variance model with probability tending to 1 under mild conditions. Simulation studies and a real example are presented to evaluate the new criterion, and it turns out that the proposed approach performs well.     

A novel variational model for image segmentation

In this paper, we propose a new variational model for image segmentation. Our model is inspired by the complex Ginzburg-Landau model and the semi-norm defined by us. This new model can detect both the convex and concave parts of images. Moreover, it can also detect non-closed edges as well as quadruple junctions. Compared with other methods, the initialization is completely automatic and the segmented images obtained by using our new model could keep fine structures and edges of the original images very effectively. Finally, numerical results show the effectiveness of our model.