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International Joint Conference on Neural Networks

作者： Rui-Zhen Gao Yu-Juan Wang Jun-Feng Lai Yong-duan Song School of Automation Chongqing University

ISBN: (纸本)9781509006212

This paper develops an adaptive control scheme for position and velocity tracking control of high speed trains under uncertain system nonlinearities and actuator failures. Neural networks with self-organizing capabilities are integrated into control design, where the number of the neurons can be adjusted online automatically, so as not only to avoid the problem inherent in the NN with fixed structure but also to deal with system uncertainties containing of nonlinear in-train forces, traction-braking nonlinearities, as well as the unknown actuation faults. As such, the resultant control algorithms are able to achieve high precision train speed and position tracking under varying operation railway conditions, as validated by theoretical analysis and numerical simulations.

关键词： high-speed train nonlinearity system uncertainties Location tracking Adaptive tracking computer algorithms design control adaptive control Theoretical analysis Fixed platforms

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Graph-Based Word Alignment for Clinical Language Evaluation

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COMPUTATIONAL LINGUISTICS 2015年第4期41卷 549-578页

作者： Prud'hommeaux, Emily Roark, Brian Rochester Inst Technol Rochester NY USA Google Inc Portland OR 97204 USA

Among the more recent applications for natural language processing algorithms has been the analysis of spoken language data for diagnostic and remedial purposes, fueled by the demand for simple, objective, and unobtrusive screening tools for neurological disorders such as dementia. The automated analysis of narrative retellings in particular shows potential as a component of such a screening tool since the ability to produce accurate and meaningful narratives is noticeably impaired in individuals with dementia and its frequent precursor, mild cognitive impairment, as well as other neurodegenerative and neurodevelopmental disorders. In this article, we present a method for extracting narrative recall scores automatically and highly accurately from a word-level alignment between a retelling and the source narrative. We propose improvements to existing machine translation-based systems for word alignment, including a novel method of word alignment relying on random walks on a graph that achieves alignment accuracy superior to that of standard expectation maximization-based techniques for word alignment in a fraction of the time required for expectation maximization. In addition, the narrative recall score features extracted from these high-quality word alignments yield diagnostic classification accuracy comparable to that achieved using manually assigned scores and significantly higher than that achieved with summary-level text similarity metrics used in other areas of NLP. These methods can be trivially adapted to spontaneous language samples elicited with non-linguistic stimuli, thereby demonstrating the flexibility and generalizability of these methods.

关键词： Natural language processing (computer science) computer algorithms Oral communication Nervous system -- Diseases Mild cognitive impairment Translations

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Congestion Control for Machine-Type Communications in LTE-A Networks

Congestion Control for Machine-Type Communications in LTE-A ...

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IEEE Global Communications Conference

作者： Chia-Wei Chang Yi-Hao Lin Yi Ren Jyh-Cheng Chen Department of Computer Science National Chiao Tung University

ISBN: (纸本)9781509013296

Collecting data from a tremendous amount of Internet-of-Things (IoT) devices for next generation networks is a big challenge. A large number of devices may lead to severe congestion in Radio Access Network (RAN) and Core Network (CN). 3GPP has specified several mechanisms to handle the congestion caused by massive amounts of devices. However, detailed settings and strategies of them are not defined in the standards and are left for operators. In this paper, we propose two congestion control algorithms which efficiently reduce the congestion. Simulation results demonstrate that the proposed algorithms can achieve 20～40% improvement regarding accept ratio, overload degree and waiting time compared with those in LTE-A.

关键词： Congestion control M2M IoT LTE-A machine to machine Next generation networks Data Collection Methods computer algorithms Communication Research Waiting time Wireless networks

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Improvement of small target detection based on tensorial filtering

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REMOTE SENSING LETTERS 2015年第10期6卷 765-774页

作者： Bourennane, S. Fossati, C. Aix Marseille Univ Ecole Cent Marseille Inst Fresnel CNRS Marseille France

Target detection is a key issue in processing hyperspectral images (HSIs). However, current spectral-identification-based algorithms are sensitive to noise during acquisition of the data. In most cases, the denoising algorithms cannot preserve small targets. In this paper, to overcome this problem, we propose a new algorithm which reduces noise to improve the target detection efficiency of HSI with small targets. First, a three-dimensional wavelet packet transform (3D-WPT) is used to decompose the HSI into several coefficient sets and models each coefficient set as a tensor. Then we exploit a powerful multilinear algebra model named parallel factor analysis (PARAFAC) to filter each tensor. The experiments conducted in both simulated and real-world hyperspectral images demonstrated the performance of the proposed method.

关键词： HYPERSPECTRAL imaging systems FILTERING theory (Signal processing) computer algorithms SIGNAL denoising DATA acquisition systems FACTOR analysis TENSOR algebra

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Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation

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COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2015年第1期2015卷 851863-851863页

作者： Du, Tingsong Hu, Yang Ke, Xianting China Three Gorges Univ Coll Sci Dept Math Yichang 443002 Peoples R China Wuhan Univ Sci & Technol Hubei Prov Key Lab Syst Sci Met Proc Wuhan 430081 Peoples R China

An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA.

关键词： computer algorithms QUANTUM theory PARTICLE swarm optimization DISTRIBUTED computing MATHEMATICAL programming

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Wavelet-artificial immune system algorithm applied to voltage disturbance diagnosis in electrical distribution systems

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IET GENERATION TRANSMISSION & DISTRIBUTION 2015年第11期9卷 1104-1111页

作者： Lima, Fernando P. A. Lotufo, Anna Diva P. Minussi, Carlos Roberto Univ Estadual Paulista Fac Engn Ilha Solteira Dept Elect Engn UNESP BR-15385000 Ilha Solteira SP Brazil

This study presents a new approach to detecting and classifying voltage disturbances in electrical distribution systems based on wavelet transform and artificial immune algorithm. This proposal unifies the negative selection artificial immune algorithm with the discrete wavelet transform concept. Thus, the measurements obtained in a distribution substation by the supervisory control and data acquisition acquisition system are transformed into the wavelet domain. Afterward, a negative selection artificial immune system realises the diagnosis, identifying and classifying the abnormalities. The principal application of this tool is to aid the system operation during faults as well as to supervise the protection system. To evaluate the performance of the proposed method, two distribution systems were modelled in EMTP software: an 84-bus test system and a 134-bus real system. The results show a good performance, emphasising the precision of the diagnosis.

关键词： ELECTRIC power distribution grids IMMUNOcomputerS ELECTRIC potential -- Measurement computer algorithms WAVELET transforms ELECTRIC power distribution -- Protection

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Gradient-based compressive sensing for noise image and video reconstruction

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IET COMMUNICATIONS 2015年第7期9卷 940-946页

作者： Zhao, Huihuang Wang, Yaonan Peng, Xiaojiang Qiao, Zhijun Hengyang Normal Univ Dept Comp Sci Hengyang Hunan Peoples R China Hunan Univ Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China Univ Texas Pan Amer Dept Math Edinburg TX 78539 USA

In this study, a fast gradient-based compressive sensing (FGB-CS) for noise image and video is proposed. Given a noise image or video, the authors first make it sparse by orthogonal transformation, and then reconstruct it by solving a convex optimisation problem with a novel gradient-based method. The main contribution is twofold. Firstly, they deal with the noise signal reconstruction as a convex minimisation problem, and propose a new compressive sensing based on gradient-based method for noise image and video. Secondly, to improve the computational efficiency of gradient-based compressive sensing, they formulate the convex optimisation of noise signal reconstruction under Lipschitz gradient and replace the iteration parameter by the Lipschitz constant. With this strategy, the convergence of our FGB-CS is reduced from O(1/k) to O(1/k(2)). Experimental results indicate that their FGB-CS method is able to achieve better performance than several classical algorithms.

关键词： COMPRESSED sensing (Signal processing) DIGITAL image processing LIPSCHITZ spaces IRREGULAR sampling (Signal processing) ITERATIVE methods (Mathematics) computer algorithms

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A Parallel Community Structure Mining Method in Big Social Networks

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MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-13页

作者： Jin, Songchang Yu, Philip S. Li, Shudong Yang, Shuqiang Natl Univ Def Technol Coll Comp Changsha 410073 Hunan Peoples R China Univ Illinois Dept Comp Sci Chicago IL 60607 USA

Community structure plays a key role in analyzing network features and helping people to dig out valuable hidden information. However, how to discover the hidden community structures is one of the biggest challenges in social network analysis, especially when the network size swells to a high level. Infomap is a top-class algorithm in nonoverlapping community structure detection. However, it is designed for single processor. When tackling large networks, its limited scalability makes it less effective in fully utilizing server resources. In this paper, based on infomap, we develop a scalable parallel nonoverlapping community detection method, Pinfomr (parallel Infomap with MapReduce), which utilizes the MapReduce framework to solve the two problems. Experiments on artificial networks and real datasets show that our parallel method has satisfying performance and scalability.

关键词： COMMUNITY organization SOCIAL networks DATA mining computer algorithms PROBLEM solving SCALABILITY (Systems engineering)

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Automatic Side-Scan Sonar Image Enhancement in Curvelet Transform Domain

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MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-14页

作者： Zhou, Yan Li, Qingwu Huo, Guanying Hohai Univ Key Lab Sensor Networks & Environm Sensing Changzhou 213022 Peoples R China Univ Guelph Sch Engn Adv Robot & Intelligent Syst ARIS Lab Guelph ON N1G 2W1 Canada

We propose a novel automatic side-scan sonar image enhancement algorithmbased on curvelet transform. The proposed algorithm uses the curvelet transform to construct a multichannel enhancement structure based on human visual system (HVS) and adopts a new adaptive nonlinear mapping scheme to modify the curvelet transform coefficients in each channel independently and automatically. Firstly, the noisy and low-contrast sonar image is decomposed into a low frequency channel and a series of high frequency channels by using curvelet transform. Secondly, a new nonlinear mapping scheme, which coincides with the logarithmic nonlinear enhancement characteristic of the HVS perception, is designed without any parameter tuning to adjust the curvelet transform coefficients in each channel. Finally, the enhanced image can be reconstructed with the modified coefficients via inverse curvelet transform. The enhancement is achieved by amplifying subtle features, improving contrast, and eliminating noise simultaneously. Experiment results show that the proposed algorithm produces better enhanced results than state-of-the-art algorithms.

关键词： IMAGE intensifiers SONAR CURVELET transforms computer algorithms MULTICHANNEL communication NONLINEAR systems

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Towards Scalable Voltage Control in Smart Grid: A Submodular Optimization Approach 16

Towards Scalable Voltage Control in Smart Grid: A Submodular...

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IEEE/ACM International Conference on Cyber-Physical Systems

作者： Zhipeng Liu Andrew Clark Phillip Lee Linda Bushnell Daniel Kirschen Radha Poovendran University of Washington Seattle WA Worcester Polytechnic Institute Worcester MA

ISBN: (纸本)9781509017737

Voltage instability occurs when a power system is unable to meet reactive power demand at one or more buses. Voltage instability events have caused several major outages and promise to become more frequent due to increasing energy demand. The future smart grid may help to ensure voltage stability by enabling rapid detection of possible voltage instability and implementation of corrective action. These corrective actions will only be effective in restoring stability if they are chosen in a timely, scalable manner. Current techniques for selecting control actions, however, rely on exhaustive search, and hence may choose an inefficient control strategy. In this paper, we propose a submodular optimization approach to designing a control strategy to prevent voltage instability at one or more buses. Our key insight is that the deviation from the desired voltage is a super-modular function of the set of reactive power injections that are employed, leading to computationally efficient control algorithms with provable optimality guarantees. Furthermore, we show that the optimality bound of our approach can be improved from 1/3 to 1/2 when the power system operates under heavy loading conditions. We demonstrate our framework through extensive simulation study on the IEEE 30 bus test case.

关键词： frequent increasing power system power systems Smart grids Reactive power control strategy VOLTAGE Motor buses optimality Scalability CASING INSPECTION Voltage stability Voltage regulation exhaustive search computer algorithms

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