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computer Science and Information Engineering, CSIE, WRI World Congress on FLAGGED

作者： Zhe Wang Songcan Chen Zhisong Pan Xuelei Ni Department of Computer Science & Engineering East China University of Science and Technology Shanghai China Department of Computer Science & Engineering Nanjing University of Aeronautics and Astronautics Nanjing China Institute of Command Automation People''s Liberation Army University of Science and Technology Nanjing China Department of Information System Shanghai Automotive Industry Corporation Shanghai China

Matrix-pattern-oriented Ho-Kashyap classifier has been demonstrated to have a superior classification performance to its vector classifier. However, it is found that the matrixized classifier takes a large computational complexity for convergence in some cases. To overcome the disadvantage, this paper introduces the early stopping technique into the matrixized Ho-Kashyap classifier and presents a matrix-pattern-oriented Ho-Kashyap classifier with early stopping named MatHKES. The presented MatHKES adopts early stopping as a new regularization technique instead of adding a regularization parameter in the criterion. The proposed algorithm achieves: 1) a less running time; 2) a competitive or better classification performance; 3) an avoidance of over fitting in training.

关键词： Feature extraction Computational complexity computer science Principal component analysis Space technology Automotive engineering Linear discriminant analysis automation Programmable logic arrays Information systems

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Study on the control strategy of economical operation in industrial boiler

Study on the control strategy of economical operation in ind...

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2nd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2008

作者： Liu, Na Zhang, Xiaoye Department of Automation Beijing Institute of Petro-Chemical Technology 19th Qingyuan Road Daxing District Huangcun Beijing China Department of Computer Application Beijing University of Chemical Technology 15th Northeast Road of Sanhua Chaoyang District Beijing China

ISBN: (纸本)9781424417483

To solve the problem of low thermal efficiency, high temperature of waste gas and high amount of carbon content in cinder and fly ash of coal-fired industrial steam boiler, at the premise of safe operation, the radiation energy signal inside furnace was introduced to research the control strategy of industrial boiler economical operation. As the radiation energy signal can provide real-time and complete reflection of combustion rate inside the stave, the optimal control loop of air-coal ratio was established to acquire the best radiation energy signal. And then according to the air-coal ratio to adjust the excess air ratio to high the thermal efficiency and low the heat losses. The results indicate that the boiler can stability operate in the optimal level and the economy obviously improve, achieve significant energy savings and pollution reduction, after the optimally adjusts the air-coal ratio.

关键词： Industrial research

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application of Wavelet Packet and Support Vector Machine to Leak Detection in Pipeline

Application of Wavelet Packet and Support Vector Machine to ...

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ISECS International Colloquium on Computing, Communication, Control, and Management, CCCM

作者： Liu Na Zhao Yanyan Department of Automation Beijing Institute of Petrochemical and Technology Beijing China Department of Computer Application Beijing University of Chemical and Technology Beijing China

Acoustic emission (AE) technology is one of the promising methods for pipeline leak detection. But AE signal of pipeline leak carry the non-stationary feature information. Therefore, one major problem is feature extraction of AE signal from noise and complexity in transmission. This paper analyzes the characteristics of AE signal to acquire effective waveform signal, applies wavelet package to construct and reconstruct signal, extracts feature vectors to set up training sample, and establishes a support vector machines (SVM) fault classifier to diagnosis. Experimental results show that the identification rate can be up to 100% for pipeline leak.

关键词： Support vector machines Feature extraction Pipelines Wavelet packets Data mining Acoustic emission Wavelet analysis

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Research on Leakage State Classification of Pipelines Based on Wavelet Packet Analysis and Support Vector Machines

Research on Leakage State Classification of Pipelines Based ...

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International Conference on Intelligent Computation technology and automation, ICICTA

作者： Na Liu Lixin Zhang Yanyan Zhao Department of Automation Beijing Institute of Petrochemical and Technology Beijing China Department of Computer Application Beijing University of Chemical and Technology Beijing China

Aimed at the problem during the pipeline leakage state detecting process, that the datum which the sensor directly surveys are quite big and the characteristic are not strong, this paper brings forward one pipeline leakage state classification method, which combines the wavelet packet analysis and support vector machines. Through using the wavelet packet to the original data, carrying on the frequency band decomposing and the energy analysis, obtains the characteristic that can most reflect the classified essence. State sorter constituted by the support vector machines, only needs a few training samples, can make signal frequency band energy as the eigenvector to recognize and classify. The experiment datum shows that, this method effectively realizes the classified recognition of leakage state.

关键词： Pipelines Wavelet analysis Wavelet packets Support vector machines Support vector machine classification Signal analysis Chemical technology automation Time frequency analysis Signal processing

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Study on the control strategy of economical operation in industrial boiler

Study on the control strategy of economical operation in ind...

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The 2nd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2008)(第二届生物信息与生物医学工程国际会议)

作者： Na Liu Xiaoye Zhang Department of Automation Beijing Institute of Petro-Chemical Technology 19th Qingyuan Road Huangcun Department of Computer Application Beijing University of Chemical Technology 15th Northeast Road of

关键词： control strategy industrial boiler radiation energy signal economical operation ezcess air ratio

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A Study on Random Autonomous Algorithm for Service Survivability Scheduling

A Study on Random Autonomous Algorithm for Service Survivabi...

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International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Lei Zhang Arun Sood Hao Dai Mingkai Ma Institute of Command Automation PLA University of Science and Technology Nanjing China Department of Computer Science and Center for Image Analysis George Mason University Fairfax VA USA Institute of Command Automation People''s Liberation Army University of Science and Technology Nanjing China Institute of China Electronic Equipment System Engineering Company Beijing China

We present in this paper a scheduling algorithm towards the service migration uncertainty that aims to enhance the service survivability in the server cluster system. Survivable scheduling algorithm is one of the important aspects of survivability study. This paper introduced the stochastic mechanism in the server cluster systems, which made it uncertain of the services migration among the servers, so as to increase the difficulty for the intruders penetrating the systems, and enhanced the system survivability. In this work, we introduced the layers of survivability study, illustrated the function of the survivable scheduling algorithm; then, analyzed the advantages and disadvantages of the exist scheduling algorithms; promoted a pseudo-random autonomous algorithm for service survivability scheduling, including generating the scheduling sequence and the Markov-based autonomous competition mechanism, the performance of the algorithm is investigated at last.

关键词： Scheduling algorithm Clustering algorithms Centralized control TCPIP Electronic equipment Systems engineering and theory Algorithm design and analysis Network servers Redundancy computer networks

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Polarity classification of public health opinions in Chinese

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2008年 5075卷 449-454页

作者： Zhang, Changli Zeng, Daniel Xu, Qingyang Xin, Xueling Mao, Wenji Wang, Fei-Yue College of Computer Science and Technology Jilin University China Institute of Automation Chinese Academy of Sciences China MIS Department University of Arizona China Artillery Command College of Shenyang China

Public health events with major consequences are occurring globally. Increasingly people are expressing their views on these events and government agencies’ responses and policies online. Recent years have seen significant interest in investigating methods to recognize favorable and unfavorable sentiments towards specific subjects, including public health opinions, from online natural language text. However, most of these efforts are focused on English. In this paper, we study Chinese opinion mining in the context of public health opinions. We explore two complementary approaches—a Chinese opinionated word-based approach and a machine learning approach. We also conduct related comparative analysis and discuss the important role Chinese NLP techniques play in polarity classification. © Springer-Verlag Berlin Heidelberg 2008.

关键词： Sentiment analysis

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Edge-enhanced speckle suppression using curvelet transform with an optimal soft thresholding

Edge-enhanced speckle suppression using curvelet transform w...

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International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

作者： Hong-Qiao Wang Fu-Chun Sun Yan-Ning Cai Zong-Tao Zhao Command Automation Departmemnt Xi''an High-tech Research Institute Xi'an China Department of computer Science and technology Tsinghua University Beijing China

Aiming at the problem that common curvelet may bring fuzzy edge when denoising, this paper proposes a novel edge-enhanced speckle suppression method using curvelet transform with an optimal soft thresholding. The method combines the original images' edge detection with the filtered image of each subband. In the edge area, first the edge information from the remnant image is extracted, and then the edge information is added to the filtered image. In the non-edge area, to increase the contrast with the edge and have a clean background, a mean filter is used to smooth the area. As a result, the edge enhanced image is gained. In order to reduce the affection of disadvantages from both hard thresholding and soft thresholding filtering to the curvelet coefficients, the method also adopts an optimal soft shresholding for filtering. The simulation results show that the de- noising method can significantly reduce the speckles while enhancing the edge and the structure of the original SAR images with more smoothness in backguound areas.

关键词： Speckle Wavelet analysis Pattern analysis Pattern recognition

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HPRS: A profitability based recommender system

HPRS: A profitability based recommender system

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IEEE International Conference on Industrial Engineering and Engineering Management

作者： Mu-Chen Chen Long-Sheng Chen Fei-Hao Hsu Yuanjia Hsu Hsiao-Ying Chou Institute of Traffic and Transportation National Chiao Tung University Taipei Taiwan Department of Information Management Chaoyang University of Technology Taichung Taiwan Institute of Commerce Automation and Managemen National Taipei University of Technology Taipei Taiwan Mobile Application Software Division High Tech Computer Corporation Taipei Taiwan

ISBN: (纸本)9781424415281;1424415284

In electronic commerce, recommender systems are popularly being used to help enterprises for satisfying customers' individually diverse preferences. These systems learn about user preferences over time and automatically suggest products that fit the learned model of user preferences. In tradition, recommendations are provided to customers based on purchase probability and customers' preferences, without considering the profitability factor for sellers. This work presents a new profitability-based recommender system, HPRS (hybrid perspective recommender system), which attempts to integrate the profitability factor into the traditional recommender systems. Comparisons between our proposed system and traditional system which only considers the purchase probability clarify the advantages of our system. The experimental results show that the proposed HPRS can increase profit from cross-selling without compromising recommendation accuracy.

关键词： Profitability Recommender systems Electronic commerce Information filtering Information filters Business Collaboration Transportation Information management Chaos

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Research on connectivity and withstand wreck on wireless Ad hoc network

Jiefangjun Ligong Daxue Xuebao/Journal of PLA University of ...

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Jiefangjun Ligong Daxue Xuebao/Journal of PLA University of Science and technology (Natural Science Edition) 2007年第2期8卷 127-132页

作者： Ma, Yu-Ping Wang, Yuan-Yuan Liu, Peng Dong, Jian-She Institute of Command Automation PLA Univ. of Sci. and Tech. Nanjing 210007 China Department of Scientific Research PLA Univ. of Sci. and Tech. Nanjing 210007 China School of Computer and Communication Lanzhou University of Technology Lanzhou 730050 China

For the purpose of persistent connection of Ad hoc network, overlay and withstand wreck must be taken into consideration. Suppose that any two nodes had to use the public transmitting nodes in order to connect to each other, by analyzing the features of the nodes in a fixed area, the model and programming method were proposed to optimize the overlay scheme, and the whole area was completely covered. According to the withstand wreck of the network, an arithmetic was proposed to replace computing probability directly by frequency, and on the basis of that, the network's capability of connection and withstand wreck was analyzed thoroughly. The result of simulating experiment proves that the capability of the network can be evaluated easily with the proposed scheme.

关键词： Ad hoc networks

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