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Chinese Automation Congress, CAC 2015

作者： Liu, Yali Cheng, Huan Jianhua, J. Li, Xi School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781467371896

In this paper, quantitative analysis was implemented to reveal the mechanism of temperature distributions inside cross-flow stack. For this purpose, a differential model of planar cross-flow SOFC stack was built. The effectiveness of this model on describing temperature distributions were full validated by experiments on single cell and a 40-cell stack. Then, the quantitative analysis was given from two aspects, namely heat produced by reactions and heat transmission between gases and solid layer. Particularly, we rigorously revealed the non-intuitive phenomenon that the fuel temperatures were decreasing inside SOFC stack along the fuel flow direction. Moreover, the research idea and the analytical method proposed in this paper also apply to co-flow and counter-flow SOFC. © 2015 IEEE.

关键词： Temperature distribution

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Optimizing application layer multicast routing via artificial fish swarm algorithm

Optimizing application layer multicast routing via artificia...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Xuan Ma Rongjun Tang Jingyan Kang Qing Liu Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China Faculty of Automation and Information Engineering

ISBN: (纸本)9781509040940

In this paper, we propose an approach based on the use of artificial fish swarm algorithm (AFSA) for solving the problem of multicast routing on application layer. Taking delay, stretch, and degree as three optimization objectives, we design the behaviors of artificial fish individual (AF), i.e. moving randomly, preying, following, and use Pareto ranking to evaluate the fitness of AF. The simulation results show that the proposed algorithm is an appropriate method to explore the search space of the complex problem and leads to good solutions in a reasonable amount of time.

关键词： Delays Routing Optimization Fish Network topology Algorithm design and analysis Visualization

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Matrix flat splicing systems 11th

Matrix flat splicing systems

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11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016

作者： Ceterchi, Rodica Pan, Linqiang Song, Bosheng Subramanian, K.G. Faculty of Mathematics and Computer Science University of Bucharest 14 Academiei Street Bucharest010014 Romania School of Electric and Information Engineering Zhengzhou University of Light Industry ZhengzhouHenan450002 China 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 Department of Mathematics Madras Christian College Chennai600059 India

ISBN: (纸本)9789811036101

In dealing with the problem of modelling DNA recombination, the operation of splicing on linear and circular strings of symbols was introduced. Inspired by splicing on circular strings, the operation of flat splicing on a pair of strings (u, v) was considered. This operation involves "cutting" u at a specified position and "inserting" v into it, with v having a pre-specified prefix as well as suffix defined by a flat splicing rule. In this work, we consider a well-known technique in formal language theory, known as "matrix of rules", and introduce matrix of flat splicing rules and thus define matrix flat splicing system (MFSS). Some results on the language generative power of MFSS are provided. An application of MFSS in the generation of chain code pictures is also pointed out. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Formal languages

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An improved reference point sampling method on Pareto optimal front

An improved reference point sampling method on Pareto optima...

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Congress on Evolutionary Computation

作者： Cheng He Linqiang Pan Hang Xu Ye Tian Xingyi Zhang Laboratory of Image Information Processing and Intelligent Control Huazhong University of Science and Technology Wuhan Hubei China Huazhong University of Science and Technology Wuhan Hubei CN Department of Computer Science Xiamen University Xiamen Fujian China Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei Anhui China

ISBN: (纸本)9781509006243

In this paper, we propose a sampling approach of reference points used for performance metrics of multi-objective evolutionary algorithms. Traditional reference point sampling methods, such as the Das and Dennis method, usually sample the reference points via a set of uniformly distributed weight vectors generated on an ideal hyper-plane in objective space, which however often ignore the geometric shape of a specific Pareto front. Therefore, we propose a novel reference point sampling approach by taking the specific shape of the Pareto optimal front to be tackled into account for measuring the performance of multi-objective evolutionary algorithms. The performance of the proposed reference point sampling method against the other two state-of-the-art sampling methods is tested on six test instances in various conditions, which clearly demonstrate the effectiveness and superiority of the proposed sampling method.

关键词： Sampling methods Shape Convergence Evolutionary computation Optimization Euclidean distance

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Displacement prediction model of landslide based on multi-gene genetic programming

Displacement prediction model of landslide based on multi-ge...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Jiejie Chen Zhigang Zeng Ping Jiang College of Computer Science and Technnology Hubei Normal university Huangshi China School of Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China Computer School Hubei PolyTechnic University Huangshi China

In this paper, a new approach is presented for predicting landslide displacement using multi-gene genetic programming (MGGP). For the characteristic of MGGP which does not need specific assumptions, two real cases is ... 详细信息

ISBN: (纸本)9781509044245

关键词： Terrain factors Mathematical model Predictive models Training Geology Computational modeling Forecasting

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Sparsity-constrained probabilistic latent semantic analysis for land cover classification

Sparsity-constrained probabilistic latent semantic analysis ...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Jun Shi Xilan Tian Zhiguo Jiang Danpei Zhao Ming Lu No. 38 Research Institute China Electronic Technology Group Corporation Hefei Anhui China Key Laboratory of Intelligent Information Processing Hefei Anhui China Beijing Key Laboratory of Digital Media Beijing China Image Processing Center Beihang University Beijing China

Land cover classification can be regarded as topic assignment that the pixels can be classified into different kinds of regions (e.g. road, tree, grass) according to the semantics of topics in topic model. In this paper, we present a novel probabilistic latent semantic analysis (pLSA) model based on sparsity constraint for classifying different kinds of land cover. In contrast with conventional topic model which usually assumes each local feature descriptor is only related to one visual word of the dictionary, our method uses sparse coding to characterize the potential relationship between the descriptor and multiple words. Therefore each descriptor can be represented by a small set of words. More importantly, we further apply sparse coding to mine the correlation of documents (i.e. image) in pLSA model. Consequently, our model can generate the more discriminative latent topics and benefit land cover classification. Experimental results on high-resolution remote sensing images demonstrate the excellent superiority of our method.

关键词： Semantics Correlation Remote sensing Probabilistic logic Dictionaries Roads image color analysis

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Aero-thermal radiation correction via multi-scale bias field estimation 3

Aero-thermal radiation correction via multi-scale bias field...

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3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015

作者： Li, Lerenhan Yan, Luxin Sang, Nong Gao, Changxin Hu, Jing Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781479961009

In this paper, a multi-scale bias field estimation is proposed to carry out the aero-thermal radiation correction. The bias field is estimated at scales from coarse to fine by an alternative minimization, after which, the degraded image is restored via subtraction. In the minimization, Tiknov regularization is employed to constrain the smoothness of bias field while Total Variation (TV) is adopted to preserve the details and structures of the latent image. Besides, Split Bregman iteration is introduced to conquer the difficulty in the non-smooth problem when resolving the minimization. Compared with conventional approaches, experiments verified that the proposed method contributes to the rapidness and precision of the algorithm. © 2015 IEEE.

关键词： Iterative methods

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DeNet: An explicit distance ensemble model for person re-identification 3

DeNet: An explicit distance ensemble model for person re-ide...

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3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015

作者： Wang, Jin Gao, Changxin Hu, Jing Sang, Nong Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781479961009

In this paper, we address the problem of person reidentification (re-id), which remains to be challenging due to view point changes, pose variations, different camera settings, etc. Different from common methods that concatenate descriptors extracted from different support regions and feature channels directly as a long vector, we encode the importance of different feature channels and support regions explicitly and propose a two-layer distance ensemble model called DeNet to measure the similarity between two images. The first layer of DeNet combines distances of different support regions while the second layer weights different feature channels. Weight parameters of DeNet are learnt under the large margin framework with the goal of maximizing the difference between distances of positive and negative matching pairs. Our method achieves very competitive results on the widely used VIPeR and PRID 450S datasets. © 2015 IEEE.

关键词： Computers

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An efficient sparse representation based classification for undersampled face recognition

An efficient sparse representation based classification for ...

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Congress on Evolutionary Computation

作者： Zizhu Fan Lipan Kang Zuoyong Li School of Basic Science East China Jiaotong University Nanchang China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou China

ISBN: (纸本)9781509006243

The typical sparse representation for classification (SRC) can obtain desirable recognition result when the training samples in each class are sufficient. Nevertheless, if the training sample set is small scale, i.e., each class has a few training samples, even single sample, the traditional SRC cannot perform well. Although one of the variants of the traditional SRC, the extended SRC(ESRC), can effectively address the above small-scale training set (SSTS) problem, its computational efficiency is very low and consequently constrains the application of the ESRC algorithm. In order to improve the computational efficiency of the ESRC algorithm, we propose a new algorithm based on coordinate descent scheme in this work. Our proposed algorithm is referred as to the fast extended SRC (FESRC) algorithm. Experiments on popular face datasets show that the FESRC algorithm can obtain the high computational efficiency without significantly degrading the recognition results.

关键词： Algorithm design and analysis Training Minimization Computational efficiency Classification algorithms Face Face recognition

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A Switching Approach to Designing Finite-Time Synchronization controllers of Coupled Neural Networks

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IEEE Transactions on Neural Networks and Learning Systems 2016年第2期27卷 471-482页

作者： Liu, Xiaoyang Su, Housheng Chen, Michael Z. Q. School of Computer Science and Technology Jiangsu Normal University Xuzhou221116 China Image Processing and Intelligent Control Key Laboratory School of Automation Huazhong University of Science and Technology Wuhan430074 China Department of Mechanical Engineering University of Hong Kong Hong Kong Hong Kong

This paper is concerned with the finite-Time synchronization issue of nonlinear coupled neural networks by designing a new switching pinning controller. For the fixed network topology and control strength, the newly d... 详细信息

关键词： Network topology

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