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Dynamic Trilateral Game Model for Attack Graph Security Game

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Dynamic Trilateral Game Model for Attack Graph Security Game

A Fuzzy-based Adaptive Genetic Algorithm and Its Case Study in Chemical Engineering

作者： Chenao Hu xuefeng yan College of Computer Sciences and Technology Nanjing University of Aeronautics and Astronautics

Internal threats have a huge impact on the attack graph security *** failure of the MTD model defence measures would be caused by the existence of internal users with certain *** trilateral game model was proposed to extend the original two-part game *** materializing internal threats,the uncertainty of two-part game model was eliminated,which was expressed as the probability equation used by the players in the observation state *** the relationship between the offensive and defensive sides became *** user strategy,based on mixed strategy game model,was proposed to increase the coupling between stealth attack and internal *** income matrix was dynamically constructed to measure the behavioural outcomes of users and *** behavioural references were obtained through dynamic *** the defender,the heuristic strategy in the model reduces the complexity of parties’ s behaviour through random *** were carried out on the attack graph model under various game *** with the two-part game model,our model’s experimental results showed that the cyber security risks were reduced by 17.9% and 18.8% respectively on the strong and weak structural attack graph.

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Chinese Journal of Chemical Engineering 2011年第2期19卷 299-307页

作者：杨传鑫颜学峰 Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai 200237 China

Considering that the performance of a genetic algorithm （GA） is affected by many factors and their rela-tionships are complex and hard to be described,a novel fuzzy-based adaptive genetic algorithm （FAGA） combined a new artificial immune system with fuzzy system theory is proposed due to the fact fuzzy theory can describe high complex *** FAGA,immune theory is used to improve the performance of selection ***,crossover probability and mutation probability are adjusted dynamically by fuzzy inferences,which are developed according to the heuristic fuzzy relationship between algorithm performances and control *** experi-ments show that FAGA can efficiently overcome shortcomings of GA,i.e.,premature and slow,and obtain better results than two typical fuzzy ***,FAGA was used for the parameters estimation of reaction kinetics model and the satisfactory result was obtained.

关键词： fuzzy logic controller genetic algorithm artificial immune system reaction kinetics model

An Immune Self-adaptive Differential Evolution Algorithm with Application to Estimate Kinetic Parameters for Homogeneous Mercury Oxidation

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Chinese Journal of Chemical Engineering 2009年第2期17卷 232-240页

作者：胡春平颜学峰 Automation Institute East China University of Science and Technology Shanghai 200237 China

A new version of differential evolution （DE） algorithm, in which immune concepts and methods are applied to determine the parameter setting, named immune self-adaptive differential evolution （ISDE）, is proposed to improve the performance of the DE algorithm. During the actual operation, ISDE seeks the optimal parameters arising from the evolutionary process, which enable ISDE to alter the algorithm for different optimization problems and improve the performance of ISDE by the control parameters＇ self-adaptation. The .performance of the proposed method is studied with the use of nine benchmark problems and compared with original DE algorithm ~nd-other well-known self-adaptive DE algorithms. The experiments conducted show that the ISDE clearly outperforms the other DE algorithms in all benchmark functions. Furthermore, ISDE is applied to develop the kinetic model for homogeneous mercury. （Hg） oxidation in flue gas, and satisfactory results are obtained.

关键词： differential evolution immune system evolutionary computation parameter estimation

基于ART-SVR的过程建模及在干点软测量中的应用

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化工学报 2008年第4期59卷 927-933页

作者：吴国庆颜学峰华东理工大学自动化研究所上海200237

针对石油化工生产过程通常呈高度非线性,且生产过程数据呈非连续、具有一定类别特性等特征,提出基于自适应谐振神经网络(adaptive resonance theory,ART)和支持向量回归(support vector regression,SVR)相结合的建模方法(ART-SVR)。首先... 详细信息

针对石油化工生产过程通常呈高度非线性,且生产过程数据呈非连续、具有一定类别特性等特征,提出基于自适应谐振神经网络(adaptive resonance theory,ART)和支持向量回归(support vector regression,SVR)相结合的建模方法(ART-SVR)。首先,基于建模样本,通过ART将样本模式空间分割成若干模式特性相近的子空间;然后,对各子空间分别采用SVR建立各自模型,实现基于样本模式空间分割的"分段"建模。仿真试验和在石脑油干点软测量建模的实际应用表明:ART-SVR模型的拟合精度和预测精度均优于全局SVR模型。

关键词：自适应谐振神经网络支持向量回归建模干点软测量

基于多元回归的对苯二甲酸加氢精制宏观动力学模型

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化学反应工程与工艺 2008年第5期24卷 468-471页

作者：胡春平颜学峰华东理工大学自动化研究所上海200237

针对在间歇反应釜钯/炭催化剂条件下对苯二甲酸(TA)加氢精制反应过程中,各反应因素对反应过程影响复杂、呈高度非线性的特征、且各种反应过程假设难免与真实机理存在出入,提出一种基于多元回归速率常数模型的加氢精制宏观动力学模型方... 详细信息

针对在间歇反应釜钯/炭催化剂条件下对苯二甲酸(TA)加氢精制反应过程中,各反应因素对反应过程影响复杂、呈高度非线性的特征、且各种反应过程假设难免与真实机理存在出入,提出一种基于多元回归速率常数模型的加氢精制宏观动力学模型方法。该动力学模型,首先基于反应步骤确定动力学模型框架;然后,应用非线性偏最小二乘回归,基于实验数据,以预测性能为指标,挖掘各反应因素与反应速率常数之间的关联模型,进而建立加氢精制反应过程宏观动力学模型。实际应用表明,所建立动力学模型具有良好的拟合精度,其平均相对误差比文献报道值低31.6%。

关键词：对苯二甲酸加氢精制偏最小二乘回归动力学模型

基于自适应偏最小二乘回归的初顶石脑油干点软测量

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化工学报 2005年第8期56卷 1511-1515页

作者：颜学峰余娟钱锋华东理工大学自动化研究所上海200237

提出了一种具有强非线性表达能力的自适应偏最小二乘回归(APLSR)方法,并应用于初顶石脑油干点软测量模型建立.APLSR对于指定的预测对象,将根据样本在自变量空间中的分布,分析它们对预测对象的预报能力,自适应地为各个样本分配权值,然后... 详细信息

提出了一种具有强非线性表达能力的自适应偏最小二乘回归(APLSR)方法,并应用于初顶石脑油干点软测量模型建立.APLSR对于指定的预测对象,将根据样本在自变量空间中的分布,分析它们对预测对象的预报能力,自适应地为各个样本分配权值,然后从加权样本数据中提取和选定PLS成分,实施自适应加权PLSR,从而获得预报性能良好的模型.同时提出将前一时刻初顶石脑油干点人工分析值引入作为模型的自变量,从而进一步提高了软测量模型的预测精度.

关键词：自适应加权回归偏最小二乘回归石脑油干点软测量

Robust incremental regularized extreme learning machine for regression problems with outliers

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Robust incremental regularized extreme learning machine for ...

第32届中国过程控制会议(CPCC2021)

作者： Yufeng Dong Tianjun Yu xuefeng yan Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and Technology

Extreme learning machine(ELM) [1],as a new learning algorithm for single hidden-layer feedforward networks(SLFNs),exhibits excellent generalization ability and rapid learning *** effect,it serves as an alternative to the gradient descent method [2] and aims to avoid slow convergence and local minima when training *** remarkable capacity of ELM induces extensive researches on it and there exist numerous improved ELM algorithms such as incremental ELM(IELM) [3],regularized ELM(RELM) [4],incremental regularized ELM(IR-ELM) [5],error minimized regularized ELM(EM-ELM) [6],and robust regularized ELM(RR-ELM) [7].They attempt to either determine optimal hidden structure or tackle with noisy ***,all these methods either fail to well handle corrupted data by outliers or to fully explore the optimal construction of hidden layer,which motivates the proposed method in this *** this study,a robust incremental regularized ELM,referred to as RIR-ELM,is presented to 1) better weaken or erase adverse impact on model performance caused by outliers in data coping with bias-variance dilemma [8] and 2) take into full consideration the structure risk minimization [9] improving model generalization *** key idea of RIR-ELM is to integrate the bias and variance of modeling errors with objective function of an incremental ELM,as well as the Frobenius norm of output weights that connect hidden nodes to output *** training a model constructed by RIR-ELM will be an optimization problem which trades off model bias against modeling error variance and structure *** RIR-ELM algorithm is implemented,an initial SLFN is built first and the output weights are calculated in analytical ***,nodes will be recursively added into hidden layer one after another and output weights will be updated simultaneously until preset conditions are *** demonstrate its performance,the proposed method is validated against IELM,EM-ELM and IR-ELM on function Si

关键词： Extreme Learning Machine Regularization Robust Incremental Outlier

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基于被动复制方式的容错CORBA模型

南京航空航天大学学报 2007年第5期39卷 612-615页

作者：杜庆伟燕雪峰南京航空航天大学信息科学与技术学院南京210016

容错CORBA(Common object request broker architecture,公共对象请求代理体系结构)是OMG(Objectmanagement group,对象管理组织)为了给分布式系统带来容错特性而对通用CORBA所作的一个扩展。文中首先介绍了基于被动复制方式的容错CORB... 详细信息

容错CORBA(Common object request broker architecture,公共对象请求代理体系结构)是OMG(Objectmanagement group,对象管理组织)为了给分布式系统带来容错特性而对通用CORBA所作的一个扩展。文中首先介绍了基于被动复制方式的容错CORBA模型——PFORBUS,针对其中主服务器的重要性,该模型提出了一个主服务器选择算法,该算法基于三角模糊数对不同服务器的可靠性进行评价,从而找出可靠性评价值最高的服务器作为主服务器。然后详细介绍了PFORBUS模型在该算法支持下的相关工作,包括系统初始化、正常工作流程及主服务器失效后的处理等。最后对该模型采用不同主服务器选择算法的情况进行了仿真,并取得了较好的效果。

关键词：公共对象请求代理体系结构容错模糊理论被动复制主复制

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阎学峰设计作品

装饰 2009年第7期 134-134页

作者：阎学峰

关键词：公益海报装饰工程