在线自适应网络异常检测系统模型与算法

随着因特网等计算机网络应用的增加,安全问题越来越突出,对具有主动防御特征的入侵检测系统的需求日趋紧迫.提出一个轻量级的在线自适应网络异常检测系统模型,给出了相关算法.系统能够对实时网络数据流进行在线学习和检测,在少量指导下逐渐构建网络的正常模式库和入侵模式库,并根据网络使用特点动态进行更新.在检测阶段,系统能够对异常数据进行报警,并识别未曾见过的新入侵.系统结构简单,计算的时间复杂度和空间复杂度都很低,满足在线处理网络数据的要求.在DARPAKDD99入侵检测数据集上进行测试,10%训练集数据和测试集数据以数据流方式顺序一次输入系统,在40s之内系统完成所有学习和检测任务,并达到检测率91.32%和误报率0.43%的结果.实验结果表明系统实用性强,检测效果令人满意,而且在识别新入侵上有良好的表现.

产品模块可再生模型与再生技术

为了满足模块化设计中产品多样化的需求,提出模块再生的思想.在模块细分的基础上提出模块元的概念.通过对模块元的分类分析以及对模块内部各模块元的功能、几何、结构信息及模块元之间的交互关系的分析,建立模块可再生模型.采用有向图与属性列表结合的方法,实现了产品更细的模块元层面的结构和属性信息的表达.利用有向图的基本运算规则,研究4种基本的模块再生技术,提出影响度函数作为衡量再生可行性的评判依据.该方法在家用电器产品开发中得到了应用验证,通过对吸尘器各模块的再生操作有效扩充了模块库,增强了产品设计的灵活性.

设备侧电压暂降严重程度评估方法研究

综合考虑ITIC曲线、SEMI曲线和C4.110工作组提出的敏感设备耐受曲线,基于严重程度函数单调性和连续性的实际分布特征,分别建立了单相、两相和三相电压暂降影响度函数;在此基础上考虑电压暂降非矩形实测波形,利用多暂降阈值描述改进影响度函数,从而提出了一种考虑电压暂降类型与多暂降阈值描述的多暂降阈值设备侧电压暂降严重程度评估方法,该评估指标综合考虑设备耐受曲线及电压暂降事件的持续时间、暂降幅值、暂降类型和暂降波形评估严重程度。实例分析验证了所提方法的正确性。

Failure probability analysis of coal crushing induced by uncertainty of influential parameters under condition of in-situ reservoir

The uncertainties of some key influence factors on coal crushing,such as rock strength,pore pressure and magnitude and orientation of three principal stresses,can lead to the uncertainty of coal crushing and make it very difficult to predict coal crushing under the condition of in-situ reservoir.To account for the uncertainty involved in coal crushing,a deterministic prediction model of coal crushing under the condition of in-situ reservoir was established based on Hoek-Brown criterion.Through this model,key influence factors on coal crushing were selected as random variables and the corresponding probability density functions were determined by combining experiment data and Latin Hypercube method.Then,to analyze the uncertainty of coal crushing,the firstorder second-moment method and the presented model were combined to address the failure probability involved in coal crushing analysis.Using the presented method,the failure probabilities of coal crushing were analyzed for WS5-5 well in Ningwu basin,China,and the relations between failure probability and the influence factors were furthermore discussed.The results show that the failure probabilities of WS5-5 CBM well vary from 0.6 to 1.0; moreover,for the coal seam section at depth of 784.3-785 m,the failure probabilities are equal to 1,which fit well with experiment results; the failure probability of coal crushing presents nonlinear growth relationships with the increase of principal stress difference and the decrease of uniaxial compressive strength.

Carbon emission impact on the operation of virtual power plant with combined heat and power system

A virtual power plant （VPP） can realize the aggregation of distributed generation in a certain region, and represent distributed generation to participate in the power market of the main grid. With the expansion of VPPs and ever-growing heat demand of consumers, managing the effect of fluctuations in the amount of available renewable resources on the operation of VPPs and maintaining an economical supply of electric power and heat energy to users have been important issues. This paper proposes the allocation of an electric boiler to realize wind power directly converted for supplying heat, which can not only overcome the limitation of beat output from a combined heat and power （CHP） unit, but also reduce carbon emissions from a VPP. After the electric boiler is considered in the VPP operation model of the combined heat and power system, a multi-objective model is built, which includes the costs of carbon emissions, total operation of the VPP and the electricity traded between the VPP and the main grid. The model is solved by the CPLEX package using the fuzzy membership function in Matlab, and a case study is presented. The power output of each unit in the case study is analyzed under four scenarios. The results show that after carbon emission is taken into account, the output of low carbon units is significantly increased, and the allocation of an electric boiler can facilitate the maximum absorption of renewable energy, which also reduces carbon emissions from the VPP.

A novel stiffness prediction method with constructed microscopic displacement field for periodic beam-like structures

This paper presents a novel stiffness prediction method for periodic beam-like structures based on the two-scale equivalence at different strain states.The macroscopic fields are achieved within the framework of Timoshenko beam theory,while the microscopic fields are obtained by the newly constructed displacement form within the framework of three-dimensional(3D)elasticity theory.The new displacement form draws lessons from that in the asymptotic homogenization method(AHM),but the present field governing equations or boundary conditions for the first two order influence functions are constructed and very different from the way they were defined in the AHM.The constructed displacement form,composed of one homogenized and two warping terms,can accurately describe the deformation mode of beam-like structures.Then,with the new displacement form,the effective stiffness is achieved by the equivalence principle of macro-and microscopic fields.The finite element formulations of the proposed method are presented,which are easy to implement.Numerical examples validate that the present method can well predict both diagonal and coupling stiffness of periodic composite beams.