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Fault Diagnosis Model Research Based on Support Vector Regression and Principal Components Analysis

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Fault Diagnosis Model Research Based on Support Vector Regre...

2010 Chinese Control and Decision Conference

作者： WenJie Tian,JiCheng Liu beijing Automation Institute of beijing Union University,beijing,China,100101

＜正＞To overcome the deficiencies of low accuracy and high false alarm rate in fault diagnosis system,a new optimization method for f the fault diagnosis model is proposed based on support vector regression（SVR）and principal components *** the character that principal components analysis algorithm can keep the discernability of original dataset after reduction,the reduces of the original dataset are calculated and used to train individual SVR classifier for ensemble,which increase the diversity between individual classifiers,and consequently,increase the detection accuracy. To validate the effectiveness of the proposed method,simulation experiments are performed based on the electronic circuit *** results show that the proposed method is a promised ensemble method owning to its high diversity,high detection accuracy and faster speed in fault diagnosis.

关键词： Support Vector Regression Principal Components Analysis Fault Diagnosis Reduction Ensemble

Fault Diagnosis Analysis with Support Vector Regression and Particle Swarm Optimization Algorithm

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Fault Diagnosis Analysis with Support Vector Regression and ...

2010 Chinese Control and Decision Conference

作者： WenJie Tian,JiCheng Liu beijing Automation Institute of beijing Union University,beijing,China,100101

＜正＞The fault diagnosis model with support vector regression（SVR） and particle swarm optimization algorithm （POSA） for is *** novel structure model has higher accuracy and faster convergence *** construct the network structure,and give the algorithm *** impact factor of fault behaviors is *** the ability of strong self-learning and faster convergence,this fault detection method can detect various fault behaviors rapidly and effectively by learning the typical fault characteristic *** the character that principal components analysis algorithm can keep the discern ability of original dataset after reduction,the reduces of the original dataset are calculated and used to train individual SVR for ensemble,and consequently,increase the detection *** validate the effectiveness of the proposed method,simulation experiments are performed based on the electronic circuit *** results show that the proposed method is a promised method owning to its high diversity,high detection accuracy and faster speed in fault diagnosis.

关键词： Support Vector Regression Principal Components Analysis Fault Diagnosis Reduction Particle Swarm Optimization Algorithm

Network Intrusion Detection Analysis with Neural Network and Particle Swarm Optimization Algorithm

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Network Intrusion Detection Analysis with Neural Network and...

2010 Chinese Control and Decision Conference

作者： WenJie Tian,JiCheng Liu beijing Automation Institute of beijing Union University,beijing,China,100101

＜正＞Because the network intrusion behaviors are characterized with uncertainty,complexity and diversity,an intrusion detection method based on neural network and particle swarm optimization algorithm（PSOA） is presented in this *** novel structure model has higher accuracy and faster convergence *** construct the network structure,and give the algorithm *** discussed and analyzed the impact factor of intrusion *** the ability of strong self-learning and faster convergence,this intrusion detection method can detect various intrusion behaviors rapidly and effectively by learning the typical intrusion characteristic *** the character that rough set can keep the discern ability of original dataset after reduction,the reduces of the original dataset are calculated and used to train neural network,which increase the detection *** apply this technique on KDD99 data set and get satisfactory *** experimental result shows that this intrusion detection method is feasible and effective.

关键词： Neural Network Rough Set Network Intrusion Reduction Particle Swarm Optimization Algorithm

Effect of Wavefront Properties on Numerical Aperture of Fresnel Hologram in Incoherent Holographic Microscopy

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Chinese Physics Letters 2014年第4期31卷 60-63页

作者： WAN Yu-Hong Institute of Information Photonics Technology Beijing University of Technology Beijing 100124 College of Applied Sciences Beijing University of Technology Beijing 100124

Fresnel incoherent correlation holographic （FINCH） microscopy is a recently developed new technique, which employs a spatial light modulator （SLM） as the beam splitter. Light originating from the same object point is split into two beams by the wavefront-division phase mask displayed on SLM, and a Fresnel-zone plate-like hologram is formed by the interference of the two beams. The numerical aperture NAH of the recorded Fresnel hologram is introduced as a comprehensive parameter for evaluating the imaging characteristics in the FINCH scheme. The effect of wavefront properties on NAH of the hologram is investigated theoretically in the sense of optimizing imaging resolution. The variation trends of NAH are described and an optimal NAH is achieved by implementing an appropriate phase mask for a given recording distance between SLM and CCD; thus optimized imaging resolution and signal-to-noise ratio are demonstrated experimentally.

关键词： FRESNEL function HOLOGRAPHY WAVEFRONTS (Optics) GIRDERS NUMERICAL apertures

A New Fuzzy Identification Approach Using Support Vector Regression and Immune Clone Selection Algorithm

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A New Fuzzy Identification Approach Using Support Vector Reg...

2009中国控制与决策会议

作者： WenJie Tian~1,Lan Ai~2,Yu Geng~3,JiCheng Liu~4 1.Automation Institute,beijing Union University,beijing,China,100101 2.Automation Institute,beijing Union University,beijing,China,100101 3.Automation Institute,beijing Union University,beijing,China,100101 4.Automation Institute,beijing Union University,beijing,China,100101

＜正＞A new fuzzy identification approach using support vector regression（SVR） and immune clone selection algorithm（ICSA） is presented in this *** positive definite reference function is utilized to construct a qualified Mercer kernel for *** an improved ICSA is developed for parameters selection of SVR,in which the number of support vectors and regression accuracy are regarded simultaneously to guarantee the conciseness of the constructed fuzzy ***,a set of TS fuzzy rules can be extracted from the SVR *** results show that the resulting fuzzy model not only costs less fuzzy rules,but also possesses good generalization ability.

关键词： Immune clone selection algorithm Fuzzy system identification Positive defmite reference function TS fuzzy rule Support vector regression.

Seismic response analysis of arch dam-water-rock foundation systems

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Earthquake Engineering and Engineering Vibration 2004年第2期3卷 283-291页

作者：杜修力王进廷 beijing key laboratory of earthquake engineering and struetural retrofit Beijing University of TechnologyBeijing 100022China Professor Department of Hydraulic Engineering Tsinghua University Beijing 100084China Assistant Professor

The effect of water compressibility on the seismic responses of arch dams is not well *** this paper,a numerical model is developed with rigorous representation of the dynamic interaction between arch dam-water- rock *** model is applied to the seismic response analysis of an arch dam with a height of 292m designed to a seismic intensity of *** is shown that consideration of the water compressibility clearly decreases the stress responses at key positions of the dam,while the added mass model gives a conservative estimate.

关键词： seismic response arch dam water compressibility dam-water-foundation interaction added mass model finite element method

Perinatal Vertical Transmission of Chikungunya Virus in Ruili, a Town on the Border between China and Myanmar

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Virologica Sinica 2021年第1期36卷 145-148页

作者： Jia-Yuan Shen Man Li Lyu Xie Jia-Rong Mao Hong-Ning Zhou Pei-Gang Wang Jin-Yong Jiang Jing An Yunnan Institute of Parasitic Diseases Simao Pu0er 665000China Ruili People’s Hospital Ruili 678600China Yunnan Provincial Key Laboratory of Vector-Borne Diseases Control and Research and Yunnan Provincial Collaborative Innovation Center for Public Health and Disease Prevention and Control(YPCICPHDPC) Simao Pu0er 665000China Department of Microbiology School of Basic Medical SciencesCapital Medical UniversityBeijing 100069China

Dear Editor,Chikungunya virus(CHIKV),an arbovirus in the family of Togaviridae,genus Alphavirus,is transmitted by the *** or *** mosquito,and causes disease in humans characterized by fever,rash,and arthralgia(Silva and Dermody 2017;Suhrbier 2019).It was first reported in 1953 in Tanzania,and caused only a few outbreaks and sporadic cases in Africa and Asia in last ***,in the epidemic in 2004,CHIKV acquired mutations that conferred enhanced transmission by the *** mosquito(Schuffenecker et al.2006).Since then,it has successively caused outbreaks in Africa,the Indian Ocean,South East Asia,the South America,and Europe(Zeller et al.2016).

关键词： al. Chi successively

Modeling and Global Conflict Analysis of Firewall Policy

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China Communications 2014年第5期11卷 124-135页

作者： LIANG Xiaoyan XIA Chunhe JIAO Jian HU Junshun LI Xiaojian Beij ing Key Laboratory of Network Technology Beihang University Beijing 100191 R R. China beijing Information Science & Technology University Beijing 100192 P. R. China Software Development Center of China Agricultural Bank Beijing 100073 P. R. China College of Computer Science and Information Technology Guangxi Normal University Guilin 541004 Guangxi Province P. R. China

The global view of firewall policy conflict is important for administrators to optimize the *** has been lack of appropriate firewall policy global conflict analysis,existing methods focus on local conflict *** research the global conflict detection algorithm in this *** presented a semantic model that captures more complete classifications of the policy using knowledge concept in rough *** on this model,we presented the global conflict formal model,and represent it with OBDD(Ordered Binary Decision Diagram).Then we developed GFPCDA(Global Firewall Policy Conflict Detection Algorithm) algorithm to detect global *** experiment,we evaluated the usability of our semantic model by eliminating the false positives and false negatives caused by incomplete policy semantic model,of a classical *** compared this algorithm with GFPCDA *** results show that GFPCDA detects conflicts more precisely and independently,and has better performance.

关键词： firewall policy semantic model conflict analysis conflict detection

Research on Structure Dynamic Neural Network

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Research on Structure Dynamic Neural Network

2008建模、辨识与控制国际会议

作者： QIAO Jun-fei College of Electronic and Control Engineering, beijing University of Technology, beijing, China. HAN Hong-gui College of Electronic and Control Engineering, beijing University of Technology, beijing, China. LI Xin-yuan College of Electronic and Control Engineering, beijing University of Technology, beijing, China.

A model of structure dynamic neural network, which is simulates the learning skills such as human beings and animals, is presented. This model contains two main steps: 1) The structure learning phase possesses the ability of online generation and ensures the number of the neural nodes of the neural network;2) The parameter learning phase adjusts the interconnection weights of neural network to achieve favourable approximation performance. The structure learning algorithm consists of growing and pruning methods, and then the Lyapunov stability theory is used to analyze the stability of this algorithm. Finally, we use this new neural network to track the nonlinear functions, simulation results show that this new algorithm can achieve favourable performance.

关键词： neural network structure structure dynamic task scheduling growing and pruning methods.