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Roedunet International Conference (RoEduNet)

作者： Mostafa Abdulghafoor Mohammed Inas Adnan Mohammed Raed.A. Hasan Nicolae Ţăpuş Ahmed Hussien Ali Omar A. Hammood Faculty of Automatic Control and Computers University Polytechnic of Bucharest/Romania The Great Emam University College Baghdad University of Information Technology and Communications / college of Engineering/ Baghdad Iraq Faculty of Al-dour Technical institute Northern Technical University Mosel IRAQ Faculty of Automatic Control and Computers University Polytechnic of Bucharest/Romania Computer Science Department AL Salam University College Baghdad Iraq Faculty of Computer Systems and Software Engineering UniversityMalaysia Pahang Malaysia

Mobile offloading is a platform that facilitates the distribution of computationally intensive tasks from mobile devices to the cloud or other devices in order to conserve energy and improve performance. The concept is practically based on the idea of exchanging relatively low communication energy for high computation power utilization. Efforts have been channeled towards energy conservation by clusters using Dynamic Power Management (DPM). This paper is a review for green energy sources for reducing energy and using energy consumption to manage sources by stating the latest studies of energy consumption and energy consumptions.

关键词： Energy consumption Task analysis Servers Energy efficiency Power system management Voltage control Cloud computing

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Modular Design of Clustering Algorithm

Modular Design of Clustering Algorithm

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2012 International Conference on computer Science and Artificial Intelligence(CSAI 2012)

作者： Zhigang Li Kunpeng Li Wenli Ma College of Computer and Automatic Control Hebei Polytechnic University Electrical Department Tangshan Vocational College of science and Technology

Currently, There are a lot of clustering algorithms in data mining areas, at the same time the new algorithms are emerging more and more. However, each algorithm in the existing mining tools is designed independently that based on their respective mind. After analyzing a large number of clustering algorithms, a conclusion is that some algorithms are designed similarly, some algorithms inherit from others. Therefore, after having summarized the design philosophy of the existing algorithms, found the correlation between them, then realizes the modular of algorithm features with the help of the object-oriented design. It is significant to increase the versatility of the code, and enhance code maintainability and future updates and maintenance of mining tools.

关键词： Data Mining, Clustering, Modular, Object-oriented

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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 International Conference on Cybernetics and Informatics, ICCI 2012

作者： Huishan, Han Yan, Liu Defang, Cheng Xue, Gao Xingtai Polytechnic College Xingtai054000 China Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao066004 China

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 cannot 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. © Springer Science+Business Media New York 2014.

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An improved method for MRAC system of indirectly designed

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2012 International Conference on Cybernetics and Informatics, ICCI 2012

作者： Han, Huishan Liu, Yan Cheng, Defang Gao, Xue Xingtai Polytechnic College Xingtai 054000 China Key Lab. of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao 066004 China

ISBN: (纸本)9781461438717

关键词： MRAC system Lyapunov theory Convergence model reference adaptive control Converge design improvement adjustable parameter Lyapunov methods plants

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Design of wireless monitor system based on CC2430 and GPRS

Design of wireless monitor system based on CC2430 and GPRS

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2012 International Conference on Teaching and Computational Science, ICTCS 2012

作者： Zeng, Xiuli Yao, Zheng Song, Xuemei College of Computer and Automatic Control Hebei United University Tangshan China

ISBN: (纸本)9783642294570

Wireless monitoring system consists of three parts: data monitoring nodes, gateway and remote monitoring center. The wireless gateway is communication center in the monitoring network between those data monitoring nodes (ZigBee network) and remote monitoring center (GPRS network). This paper makes a research on a kind of mobile nodes based on the MSP430 and CC2430 dual architectures, and researches on a wireless gateway for the wireless monitoring system and designs its software and hardware system. The experimental results show that the locations of nodes has lower computational complexity, higher positioning accuracy and stronger robustness. © 2012 Springer-Verlag GmbH.

关键词： Sensor nodes

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Intelligent control System of Stack-boiler

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Physics Procedia 2012年 25卷 1205-1211页

作者： Li Jing Niu Jingxia Lang Jianhua Li Shaofeng Li Zhi College of Light Industry Hebei Polytechnic University Tangshan China Intelligent Instrument Factory Hebei Polytechnic University Tangshan China College of Mechanical Engineering Hebei United University Tangshan China College of Computer and Automatic Control Hebei United University Tangshan China

Boiler combustion control system's basic task is to make fuel burn calories adapt to the needs of the water temperature and ensure the economical combustion and the safe operation. In the foundations which have analyzed the stack-boiler's work process and control system structure, the system designed by using the self-learning and self-optimizing fuzzy control system of the PC to make air/coal ratio achieve the best and realize the optimized combustion; through PLC to accelerate the speed of response to the boiler, and speed up the PC to optimize the speed and realize the double loop control system for stack-boiler. The control system in premise of the stack-boiler reaches the goal of the load to achieve the highest efficiency of the boiler combustion.

关键词： stack-boiler control systemt self-learning self-optimizing fuzzy control

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Intelligent control System of Stack-boiler

Intelligent Control System of Stack-boiler

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2012 International Conference on Solid State Devices and Materials Science(SSDMS 2012)

作者： Li Jing Niu Jingxia Lang Jianhua Li Shaofeng Li Zhi College of Light Industry Hebei Polytechnic University Intelligent Instrument Factory Hebei Polytechnic University College of Mechanical Engineering Hebei United University College of Computer and Automatic Control Hebei United University

Boiler combustion control system's basic task is to make fuel burn calories adapt to the needs of the water temperature and ensure the economical combustion and the safe operation. In the foundations which have analyzed the stack-boiler's work process and control system structure, the system designed by using the self-learning and selfoptimizing fuzzy control system of the PC to make air/coal ratio achieve the best and realize the optimized combustion;through PLC to accelerate the speed of response to the boiler, and speed up the PC to optimize the speed and realize the double loop control system for stack-boiler. The control system in premise of the stack-boiler reaches the goal of the load to achieve the highest efficiency of the boiler combustion.

关键词： stack-boiler control systemt self-learning self-optimizing fuzzy control

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Bionic Robot control based on Advanced Updating

Bionic Robot Control based on Advanced Updating

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2010 3rd International Conference on computer and Electrical Engineering(ICCEE 2010)

作者： Tao Shi Zhikun Chen College of Computer & Automation Control Hebei Polytechnic University

In view of the balance control problem of self-balance robot, the reinforcement learning mechanism based on the advanced updating is proposed as a self-balance bionic learning algorithm of the robot. This algorithm can choose optimal behavior above the baseline with the certain probability by using baseline in the advanced updating and unifying the probability curiosity mechanism in reinforcement learning, so that the robot can obtain the bionic self-learning skills like creature under the unknown environment, and realize the bionic self-balance controls of the robot. Finally, the simulation experiment is made. The result indicates that the robot can obtain the stronger self-learning skills about the balance control and the better dynamic performance from this learning algorithm of the reinforcement learning based on the advanced updating and it manifests the bionic characteristic about the advanced updating, and gains the higher research and the application value.

关键词： Advanced updating reinforcement learning curiosity mechanism bionic robot

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Research on Neural Network Model Based on Subtraction Clustering and Its Applications

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Physics Procedia 2012年 25卷 1642-1647页

作者： Zhang Tie-jun Chen Duo Sun Jie Department of Computer Science and Technology Tangshan CollegeTangshan Hebei Province China School of Computer and Control Hebei Polytechnic University Tangshan Hebei Province China

This paper takes advantage of the integration of subtraction clustering and fuzzy c-means clustering algorithm to obtain precise number of clusters and the degree of membership, and establishes the neural network model based on the multiple criterion information fusion and the fuzzy technology. Collecting a variety of data in actual underground mining process and integrating them as a whole, the simulations are performed. Experimental results indicate that the proposed method is valid.

关键词： subtractive clustering fuzzy c-means clustering fuzzy neural network

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Research on Neural Network Model Based on Subtraction Clustering and Its Applications

Research on Neural Network Model Based on Subtraction Cluste...

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2012 International Conference on Solid State Devices and Materials Science(SSDMS 2012)

作者： ZHANG Tie-jun CHEN Duo SUN Jie Department of Computer Science and Technology Tangshan College School of Computer and Control Hebei Polytechnic University

关键词： subtractive clustering fuzzy c-means clustering fuzzy neural network

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