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2018 International Conference on Computer Science and Software Engineering (CSSE 2018)

作者： Taizhang Shang Xiang Xia Jun Zheng School of Automation Huazhong University of Science and Technology (HUST) Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education

The K Nearest Neighbor(KNN) classifier has been widely used in the applications of data mining and machine learning, because of its simple implementation and distinguished performance. However, because the distance between all training samples and test samples have to be calculated, when there are too many samples or samples have huge features dimensionality, the time complexity and space complexity are high. The paper proposes a KNN algorithm with the minimum intra-class distance and the maximum extra-class distance(MIME-KNN). By finding a transformation matrix, the algorithm minimizes the intra-class distance and maximizes the distance between classes, which can improve the classification performance of traditional KNN algorithm. At the same time, the algorithm will also reduce the dimensionality of the samples to achieve the purpose of reducing time and space complexity. Experimental results show that the MIME-KNN work well in practical.

关键词： MIME-KNN Improve KNN Classifier Performance Include Classification Accuracy and Time Consumption

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Unsupervised Ensemble Learning for Class Imbalance Problems

Unsupervised Ensemble Learning for Class Imbalance Problems

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Chinese Automation Congress

作者： Zihan Liu Dongrui Wu Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan China

Ensemble learning, which aggregates multiple base (weak) learners to obtain a strong learner, is an effective approach for improving the generalization performance of a machine learning model. Several completely unsupervised ensemble learning approaches have been proposed in the literature for binary classification. However, most of them only considered the case that the two classes are balanced, and hence their performances deteriorate when there is significant class imbalance, which often happens in practice. This paper proposes a spectral meta-learner for class imbalance (SMLCI) approach to explicitly consider the class imbalance. Experiments on 12 UCI datasets from various domains verified that SMLCI significantly outperformed the individual base classifiers, and also five existing unsupervised ensemble learning approaches, when the balanced classification accuracy is used as the performance measure.

关键词： Ensemble learning Unsupervised learning Class imbalance Binary classification

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A WOA-based algorithm for parameter optimization of support vector regression and its application to condition prognostics 36

A WOA-based algorithm for parameter optimization of support ...

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第36届中国控制会议

作者： LI Sai FANG Huajing School of Automation Key Laboratory of Image Processing and Intelligent ControlMinistry of EducationHuazhong University of Science and Technology

ISBN: (纸本)9781538629185

Condition monitoring is very important for system safety and condition-based *** series prediction capabilities of machine learning like support vector regression(SVR) can be utilized for ***,choosing optimal parameters for SVR is an important step in SVR model design,which heavily affects the performance of ***,a whale optimization algorithm(WOA) based algorithm is proposed for SVR parameters *** proposed algorithm has been evaluated through some benchmark ***,the proposed method with moving window technology is used to condition prognostics of the Tennessee Eastman *** and engineering application show that the SVR-WOA method is effective,by noting that the computation time is shortened in some application scenarios.

关键词： Support vector regression Whale optimization algorithm Parameter optimization Condition prognostics

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A battery management system with two-stage equalization 29

A battery management system with two-stage equalization

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第29届中国控制与决策会议

作者： Shengping Hong Jianhua Jiang Xi Li School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent ControlHuazhong University of Science & Technology

ISBN: (纸本)9781509046584

This paper presents a lithium-ion battery pack equalization system and method. The batteries are divided into several groups, which are connected in parallel with the bidirectional DC-DC converters respectively, and the output of DC-DC converters ends are connected in series with each other as a DC bus. The scheme divides equalization of the cells into two stages: intra-group equalization and inter-group equalization, and the two stages are respectively realized by battery time-sharing-access structure and stack energy-sharing structure. Then equalization strategy of the distributed battery energy storage system under two stages is proposed, especially the Single Cell Battery Access Timing Algorithm and MPC Algorithm. The simulation results show that the proposed battery management structure and control strategy can realize fast and accurate SOC equalization.

关键词： Battery management system(BMS) cell equalization battery time-sharing-access structure stack energy-sharing structure Single Cell Battery Access Timing Algorithm MPC Algorithm

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Recommendations on Designing Practical Interval Type-2 Fuzzy Systems

arXiv

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arXiv 2019年

作者： Wu, Dongrui Mendel, Jerry M. Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Ming Hsieh Department of Electrical Engineering University of Southern California Los AngelesCA United States College of Artificial Intelligence Tianjin Normal University Tianjin China

Interval type-2 (IT2) fuzzy systems have become increasingly popular in the last 20 years. They have demonstrated superior performance in many applications. However, the operation of an IT2 fuzzy system is more complex than that of its type-1 counterpart. There are many questions to be answered in designing an IT2 fuzzy system: Should singleton or non-singleton fuzzifier be used? How many membership functions (MFs) should be used for each input? Should Gaussian or piecewise linear MFs be used? Should Mamdani or Takagi-Sugeno-Kang (TSK) inference be used? Should minimum or product t-norm be used? Should type-reduction be used or not? How to optimize the IT2 fuzzy system? These questions may look overwhelming and confusing to IT2 beginners. In this paper we recommend some representative starting choices for an IT2 fuzzy system design, which hopefully will make IT2 fuzzy systems more accessible to IT2 fuzzy system designers. Copyright © 2019, The Authors. All rights reserved.

关键词： Membership functions

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Center Difference Set Membership Filter by Zonotopes for Nonlinear System

Center Difference Set Membership Filter by Zonotopes for Non...

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International Conference on Modelling, Identification and control (ICMIC)

作者： Rong Cheng Jian Huang Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei P.R. China

The paper proposes an improved approach to state estimation for nonlinear discrete-time systems based on zonotopes. To overcome the inherent defect of Taylors formula, a lower-order multi-dimensional extension of Stirling's interpolation formula is used to realize the linearization of nonlinear models. A nonlinear programming method is used to optimize the guaranteed margin of linearization error to obtain a more compact bound estimation, thereby reducing the conservativeness of the algorithm. Simulation results have shown the effectiveness and improved performance of the proposed algorithm.

关键词： state estimation Taylor series Kalman filters Strips Nonlinear systems Interpolation Noise measurement

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Automatic Reading System for Analog Instruments Based on Computer Vision and Inspection Robot for Power Plant

Automatic Reading System for Analog Instruments Based on Com...

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International Conference on Modelling, Identification and control (ICMIC)

作者： Junzhe Wang Jian Huang Rong Cheng Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei P.R. China

In this paper, an automatic reading system for analog instruments has been designed for monitoring in power plants. In a general automatic reading system, there are many limitations to the reading correctness and system robustness such as the high cost for the reason that there is only one instrument could be monitored by a single system, the strict restrict of the camera angle, and being not suitable for instruments with dense scales and so on. We present some solutions to overcome these limitations. Firstly, we combine a mobile inspection robot with an image capture device and the image processing method to cut the cost of the monitoring of analog instruments in power plants. Then, we use Hough transform and perspective transform to correct the geometric distortion of images caused by camera angle. Eventually, we get the result of dense scaled instruments based on polar transform. Experiments show that our system performs quite well, and the reading error is less than the results which obtained from the general automatic reading system.

关键词： Instruments Cameras Inspection Robot kinematics Transforms Monitoring

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Tissue P systems with rule production/removal 18th

Tissue P systems with rule production/removal

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18th International Conference on Membrane Computing, CMC 1018

作者： Pan, Linqiang Song, Bosheng Zhang, Gexiang Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology WuhanHubei430074 China School of Electric and Information Engineering Zhengzhou University of Light Industry ZhengzhouHenan450002 China Robotics Research Center and Key Laboratory of Fluid and Power Machinery Xihua University Chengdu610039 China

ISBN: (纸本)9783319733586

Tissue P systems are computational models inspired by the way of biochemical substance movement/exchange between two cells or between a cell and the environment, where all communication (symport/antiport) rules used in a system are initially set up and keep unchanged during any computation. In this work, a variant of tissue P systems, called tissue P systems with rule production/removal (abbreviated as TRPR P systems) is considered, where rules in a system are dynamically changed during a computation, that is, at any computation step new rules can be produced and some existing rules can be removed. The computation power of TRPR P systems is investigated. It is proved that Turing universality is achieved for TRPR P systems with one cell, and using symport rules of length at most 1, antiport rules of length at most 2 or symport rules of length at most 2 and working in a maximally parallel manner. We further show that TRPR P systems with two cells, using symport rules of length at most 1, and working in a flat maximally parallel manner, are Turing universal. © 2018, Springer International Publishing AG.

关键词： Cells

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Tiny noise, big mistakes: Adversarial perturbations induce errors in Brain-Computer Interface spellers

arXiv

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arXiv 2020年

作者： Zhang, Xiao Wu, Dongrui Ding, Lieyun Luo, Hanbin Lin, Chin-Teng Jung, Tzyy-Ping Chavarriaga, Ricardo Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China School of Civil Engineering and Mechanics Huazhong University of Science and Technology Wuhan430074 China Centre of Artificial Intelligence Faculty of Engineering and Information Technology University of Technology Sydney Sydney2007 Australia La Jolla CA92093 United States Center for Advanced Neurological Engineering Institute of Engineering in Medicine UCSD La Jolla CA92093 United States ZHAW DataLab Zürich University of Applied Sciences Winterthur8401 Switzerland

An electroencephalogram (EEG) based brain-computer interface (BCI) speller allows a user to input text to a computer by thought. It is particularly useful to severely disabled individuals, e.g., amyotrophic lateral sclerosis patients, who have no other effective means of communication with another person or a computer. Most studies so far focused on making EEG-based BCI spellers faster and more reliable;however, few have considered their security. This study, for the first time, shows that P300 and steady-state visual evoked potential BCI spellers are very vulnerable, i.e., they can be severely attacked by adversarial perturbations, which are too tiny to be noticed when added to EEG signals, but can mislead the spellers to spell anything the attacker wants. The consequence could range from merely user frustration to severe misdiagnosis in clinical applications. We hope our research can attract more attention to the security of EEG-based BCI spellers, and more broadly, EEG-based BCIs, which has received little attention before. Copyright © 2020, The Authors. All rights reserved.

关键词： Electroencephalography

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Affect estimation in 3d space using multi-task active learning for regression

arXiv

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arXiv 2018年

作者： Wu, Dongrui Huang, Jian Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

—Acquisition of labeled training samples for affective computing is usually costly and time-consuming, as affects are intrinsically subjective, subtle and uncertain, and hence multiple human assessors are needed to evaluate each affective sample. Particularly, for affect estimation in the 3D space of valence, arousal and dominance, each assessor has to perform the evaluations in three dimensions, which makes the labeling problem even more challenging. Many sophisticated machine learning approaches have been proposed to reduce the data labeling requirement in various other domains, but so far few have considered affective computing. This paper proposes two multi-task active learning for regression approaches, which select the most beneficial samples to label, by considering the three affect primitives simultaneously. Experimental results on the VAM corpus demonstrated that our optimal sample selection approaches can result in better estimation performance than random selection and several traditional single-task active learning approaches. Thus, they can help alleviate the data labeling problem in affective computing, i.e., better estimation performance can be obtained from fewer labeling queries. Copyright © 2018, The Authors. All rights reserved.

关键词： Regression analysis

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