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5th International Conference on control and Automation, ICCA'05

作者： Sun, Chuan Wang, Yongji Zhu, Xiangou Dept. of Mechanic and Dynamic Engineering HuangShi Polytechnic College 435003 HuangShi HuBei China Dept. of Automatic Control Huazhong University of Science and Technology 430074 Wuhan HuBei China College of Computer Science and Engineering WenZhou University 325027 WenZhou ZheJiang China

ISBN: (纸本)0780391381

In this paper, using the fuzzy theory and gray theory, a concept of the degree of fuzzy infection and a new reliability analysis method based on the relation of fuzzy infection were proposed, and the mathematical mode of series connection and parallel connection system was first set up and their rationalities were proven. An illustrational example was given to demonstrate the effectiveness of this theory. © 2005 IEEE.

关键词： System stability

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automatic removal algorithm of electrooculographic artifacts in non-invasive braincomputer interface based on independent component analysis

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Shengwu Yixue Gongchengxue Zazhi/Journal of Biomedical Engineering 2022年第6期39卷 1074-1081页

作者： Song, Hao Xu, Song Liu, Guoming Liu, Jing Xiong, Peng Key Laboratory of Digital Medical Engineering of Hebei Province Hebei Baoding071002 China School of Quality and Technical Supervision Hebei University Hebei Baoding071002 China Beijing Aerospace Automatic Control Institute Beijing100854 China National Key Laboratory of Aerospace Intelligent Control Technology Beijing100854 China College of Computer and Cyber Security Hebei Normal University Shijiazhuang050024 China College of Electronic and Information Engineering Hebei University Hebei Baoding071002 China

The non-invasive brain-computer interface (BCI) has gradually become a hot spot of current research, and it has been applied in many fields such as mental disorder detection and physiological monitoring. However, the electroencephalography (EEG) signals required by the non-invasive BCI can be easily contaminated by electrooculographic (EOG) artifacts, which seriously affects the analysis of EEG signals. Therefore, this paper proposed an improved independent component analysis method combined with a frequency filter, which automatically recognizes artifact components based on the correlation coefficient and kurtosis dual threshold. In this method, the frequency difference between EOG and EEG was used to remove the EOG information in the artifact component through frequency filter, so as to retain more EEG information. The experimental results on the public datasets and our laboratory data showed that the method in this paper could effectively improve the effect of EOG artifact removal and improve the loss of EEG information, which is helpful for the promotion of non-invasive BCI. © 2022 West China Hospital, Sichuan Institute of Biomedical Engineering. All rights reserved.

关键词： Electroencephalography

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An Improved Method for MRAC System of Indirectly Designed

An Improved Method for MRAC System of Indirectly Designed

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2012年控制与信息国际会议

作者： Huishan Han Yan Liu Defang Cheng Xue Gao Xingtai Polytechnic College Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

Based on Lyapunov stability theorem, a MRAC system was researched to solve that differential value of plant output is unknown. Meanwhile an improved design for MRAC system aimed on the factor of restricting convergence of system is given. The method not only solves the problem that makes the system can not work well as a result of the adjustable parameters, but also improves the convergence of plant. The simulation graphs have shown that the plant can follow the output of the reference model quit well

关键词： MRAC system · Lyapunov theory · Convergence

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Traditional Chinese Medicine Health Status Identification with Graph Attention Network 1

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4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Fu, Amin Ma, Jishun Wang, Chuansheng Zhou, Changen Li, Zuoyong Teng, Shenghua College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao266590 China Department of Automatic Control Technical Polytechnic University of Catalonia Barcelona08034 Spain Research Base of Traditional Chinese Medicine Syndrome Fujian University of Traditional Chinese Medicine Fuzhou350122 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China

ISBN: (数字)9783031200960

ISBN: (纸本)9783031200953

The Traditional Chinese Medicine Health Status Identification plays an important role in TCM diagnosis and prescription recommendation. In this paper, we propose a method of Status Identification via Graph Attention Network, named SIGAT, which captures the complex medical correlation in the symptom-syndrome graph. More specifically, we construct a symptom-syndrome graph in that symptoms are taken as nodes and the edges are connected by syndromes. And we realize automatic induction of symptom to state element classification by using the attention mechanism and perceptron classifier. Finally, we conduct experiments by using hamming loss, coverage, 0/1 error, ranking loss, average precision, macro-F1 score, and micro-F1 score as evaluation metrics. The results demonstrate that the SIGAT model outperforms comparison algorithms on Traditional Chinese Medicine Prescription Dictionary dataset. The case study results suggest that the proposed method is a valuable way to identify the state element. The application of the graph attention network classification algorithm in TCM health status identification is of high precision and methodological feasibility. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Classification (of information)

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Implementation of Metadata Warehouse Used in a Distributed Data Mining Tool

Implementation of Metadata Warehouse Used in a Distributed D...

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International Conference on Challenges in Environmental Science and computer Engineering (CESCE)

作者： Yuekun Ma Shuli Yu Dongyan Li Lina Liu College of Computer and Automatic Control Hebei Polytechnic University Tangshan China Tangshan Modern Control Limited Tangshan China MCC Jingtang Construction Corporation Limited Tangshan China Tangshan commemorative museum Tangshan China

ISBN: (纸本)9781424459230;9780769539720

The application of data mining in the area of control systems provides a perfect solution for the obtaining of the control rules fully and accurately. As author, we have discussed some questions on this distributed data mining tool used in control system in some paper. In this paper, some detail technologies and methods to implement the Metadata warehouse used in that distributed data mining tool will be introduced. The main content in the paper will be include composing and Manifestations of the system Metadata warehouse and the information maintenance method of it . Besides, the expression of data source, data mining algorithm, result of data mining (knowledge) and calculation resource in metadata are also discussed. Making full use of the Metadata warehouse, the data mining tool can reduce time of communication in the distributional data mining process greatly and enhance the system's efficiency.

关键词： Data mining control systems automatic control Uniform resource locators Distributed computing Databases Earthquake engineering Data engineering Educational institutions Application software

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Design and Implementation of Schedule Module in a Distributed Data Mining Tool

Design and Implementation of Schedule Module in a Distribute...

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International Conference on Challenges in Environmental Science and computer Engineering (CESCE)

作者： Yuekun Ma Shuli Yu Lina Liu Dongyan Li College of Computer and Automatic Control Hebei Polytechnic University Tangshan China Tangshan Modern Control Limited Tangshan China Tangshan commemorative museum Tangshan China MCC Jingtang Construction Corporation Limited Tangshan China

ISBN: (纸本)9781424459230;9780769539720

The application of data mining in the area of control systems provides a perfect solution for the obtaining of the control rules fully and accurately. As author, we have discussed some questions on this distributed data mining tool used in control system in some paper, which include the architecture, Computation pattern, database auto-connection, simple mining mechanism and main function of the distributed data mining tool. In this paper, scheduling model of a data mining tool that can be used to obtain control rules will be introduced. The main content in the paper will be include some detail implementation technologies and methods used in the distributed data mining tool's scheduling model.

关键词： Data mining Processor scheduling control systems Distributed computing automatic control Grid computing computer architecture Earthquake engineering Data engineering Design engineering

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Study of The Cost-sensitive AdaBoost Face Detection Algorithm

Study of The Cost-sensitive AdaBoost Face Detection Algorith...

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The 2010 International Conference on computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

作者： Dingli Song BingruYang FuxingYu School of Information Engineering University of Science and Technology Beijing Beijing China Colleg School of Information Engineering University of Science and Technology Beijing Beijing China College of Computer and Automatic Control Hebei Polytechnic University

ISBN: (纸本)9781424472352

It is the mainstream method that in human face detection and recognition with AdaBoost as the representative based on statistical learning method. Detection rates have reached a high level, and can achieve real-time detection. However, AdaBoost algorithm treats equally for different categories, there is no distinction between the cost of the different error categories. This paper presents a new cost-sensitive Ada Boost-based face detection algorithm, ensuring the detection rate and speed, effectively reducing the false detection rate, and improving the detection accuracy.

关键词： cost-sensitive face detection cascade classifier adaboost

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Design and implement of neural network based fractional order PIα controller

Design and implement of neural network based fractional orde...

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International Conference on Natural Computation (ICNC)

作者： Ruikun Gong Youliang Yang Yansong Tian Guangxiang Zhang Jie Sun Lei Chen College of Computer and Automatic Control Hebei Polytechnic University No.46 Xinhua West Road Lunan District Tangshan 063009China Gratuate School Hebei Polytechnic University No.46 Xinhua West Road Lunan District Tangshan 063009China

Traditional Ractional-order PI λ D μ controller is more flexible and gives an opportunity to better adjust the dynamical properties of a fractional-order control system than the traditional PID controller. However, the selection of controller parameters is more difficult for fractional-order PI λ D μ controller which introduces additional two parameters λ and μ. For better adaptive capacity of system uncertainty without generality loss, a fractional-order PI α controller with self-tuning parameters is presented based on neural network. The discretization method used and the material design method of fractional-order PI α controller are described, and the architecture of back-propagat ion neural networks and parameters self-tuning algorithm of the controller are discussed indetail. The experiment results show that the controller presented can maintain the performance of the normal fractional-order controller, while possesses better flexibility and parameters self-tuning ability.

关键词： Artificial neural networks Fractional calculus Roads control systems Educational institutions Equations

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System reliability calculation based on RBF neural network

System reliability calculation based on RBF neural network

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International Conference on computer Application and System Modeling (ICCASM)

作者： Yanbin Han Guangchen Bai Xiaoying Li School of Jet Propulsion Beijing University of Aeronautics & Astronautics Beijing China Computer and Automatic Control College Hebei Polytechnical University Tangshan China

In order to improve the calculation accuracy of structural system failure probability, RBF neural networks which is based on the failure probability data calculated accurately can simulate into the four-dimensional space neural network of a single output neuron and three input neurons because system failure probability is related to reliability index, failure mode number and the correlation coefficient among the failure modes. As long as the networks meet the accuracy requirements and the training is completed, calculating neural network of system failure probability comes into being. The vector which is formed by the reliability index, failure mode number and the correlation coefficient is fed into the neural network, and then the probability of system failure can be accurately figured out. This method has high precision, the computational efficiency of fast and practical value in engineering calculations.

关键词： Artificial neural networks computer languages Estimation Approximation methods

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Research on information fusion model based on multi-clustering fuzzy neural networks

Research on information fusion model based on multi-clusteri...

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International Symposium on Knowledge Acquisition and Modeling, KAM

作者： Tie-jun Zhang Duo Chen Xiao-yue Liu Department of Computer Science and Technology Tangshan Teacher''s College Tangshan Hebei China Department of Computer Science and Technology Tangshan College Tangshan Hebei Province China School of Computer and Control Hebei Polytechnic University Tangshan China

Aiming at modeling of the complex and large industrial process, this paper proposes the multi-clustering based on the fusion of hierarchical clustering algorithm of field potential topology and fuzzy c-means clustering, on which the structure of fuzzy neural network model is determined. According to the membership degree calculated, the fuzzy neural network model has been configured based on the multi criteria information fusion and fuzzy technology. Simulation results verify the validity of the model, which has some reference value and significance on the coal mining.

关键词： Educational institutions

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