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Interval prediction of responses for uncertain multidisciplinary system

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2017年第6期55卷 1945-1964页

作者： Wang, Xiaojun Wang, Ruixing Chen, Xianjia Wang, Lei Geng, Xinyu Fan, Weichao Beihang Univ Inst Solid Mech Beijing 100083 Peoples R China

Considering that numerous sample data points are required in the probabilistic method, a non-probabilistic interval analysis method can be an alternative when the information is insufficient. In the paper, new strategies, which are iterative algorithm based interval uncertainty analysis methods (IA-IUAMs), are developed to acquire the bounds of the responses in multidisciplinary system. Two iterative processes, Jacobi iteration and Seidel iteration, are applied in the new methods respectively. The Jacobi iteration based interval uncertainty analysis method (JI-IUAM) utilizes the strategy of concurrent subsystem analysis to improve computational efficiency while the Seidel iteration based interval uncertainty analysis method (SI-IUAM) can accelerate convergence by utilizing the newest information. Both IA-IUAMs are able to evaluate the bounds of responses accurately and quickly. The presented methods are compared with general sensitivity analysis based interval uncertainty analysis method (SIUAM) and conventional Monte Carlo simulation approach (MCS). The validity and efficiency of the new methods are demonstrated by two numerical examples and two engineering examples. Results show that, on the one hand, IA-IUAMs are more efficient than MCS by avoiding hundreds of system analyses, on the other hand, IA-IUAMs are more accurate and have a wider range of application than SIUAM by avoiding linear approximation and global sensitivity calculation.

关键词： Interval uncertainty analysis Multidisciplinary system iterative algorithm Jacobi iteration Seidel iteration

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Aiming strategy model based on allowable flux densities for molten salt central receivers

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SOLAR ENERGY 2017年 157卷 1130-1144页

作者： Sanchez-Gonzalez, Alberto Reyes Rodriguez-Sanchez, Maria Santana, Domingo Univ Carlos III Madrid Dept Thermal & Fluid Engn Av Univ 30 Madrid 28911 Spain

This study presents an aiming model to properly point heliostats at cylindrical molten salt receivers in Solar Power Tower. By means of two iterative algorithms (search and fit), the proposed strategy attempts to maximize the receiver thermal power output while preserving the receiver operational limits. Corrosion and thermal stress constraints are translated into allowable flux densities (AFD) that are handled by the model. The computer code accommodates the flux images produced by each heliostat in a field to accurately fit the AFD limit. In this paper, a Gemasolar-like field receiver system serves to illustrate the aiming model. Compared to the equatorial aiming, receiver interception is slightly lower using the proposed strategy, but the receiver integrity is ensured;peak flux is significantly reduced up to 23%. It has been found that a favorable flux density profile generally has its peak displaced to the salt entrance at each receiver panel. Since external cylindrical receivers consist of a combination of up-flow and down-flow panels, the optimal flux profile is challenging for contiguous panels with contrary demands. In spite of that, remarkable matching is achieved by the fit algorithm. Because of its fast computation and automatic operation, the resulting tool can be applied to real-time control of existing heliostat fields and the integrated design of the coupled systems field and receiver. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Interaction field receiver Heliostat aim point iterative algorithm Corrosion and thermal stress

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Fast graph clustering with a new description model for community detection

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INFORMATION SCIENCES 2017年 388卷 37-47页

作者： Bai, Liang Cheng, Xueqi Liang, Jiye Guo, Yike Shanxi Univ Sch Comp & Informat Technol Taiyuan 030006 Shanxi Peoples R China Chinese Acad Sci Inst Comp Technol Beijing 100190 Peoples R China Imperial Coll London Dept Comp London SW7 England

Efficiently describing and discovering communities in a network is an important research concept for graph clustering. In the paper, we present a community description model that evaluates the local importance of a node in a community and its importance concentration in all communities to reflect its representability to the community. Based on the description model, we propose a new evaluation criterion and an iterative search algorithm for community detection (ISCD). The new algorithm can quickly discover communities in a large-scale network, due to the average linear-time complexity with the number of edges. Furthermore, we provide an initial method of input parameters including the number of communities and the initial partition before algorithm implementation, which can enhance the local-search quality of the iterative algorithm. The proposed algorithm with the initial method is called ISCD+. Finally, we compare the effectiveness and efficiency of the ISCD+ algorithm with six representative algorithms on several real network data sets. The experimental results illustrate that the proposed algorithm is suitable to address large-scale networks. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Graph clustering Community detection Community description model Evaluation criterion iterative algorithm

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Modal parameter identification by an iterative approach and by the state space model

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2017年 95卷 239-251页

作者： Lardies, Joseph Univ Bourgogne Franche Comte CNRS UFC ENSMM UTBM FEMTO ST Inst Dept Appl Mech F-25000 Besancon France

The problem of estimating a spectral representation of exponentially decaying signals from a set of sampled data is of considerable interest in several applications such as in vibration analysis of mechanical systems. In this paper we present a nonparametric and a parametric method for modal parameter identification of vibrating systems when only output data is available. The nonparametric method uses an iterative adaptive algorithm based in the formation of a two dimensional grid mesh, both in frequency and damping domains. We formulate the identification problem as an optimization problem where the signal energy is obtained from each frequency grid point and damping grid point. The modal parameters are then obtained by minimizing the signal energy from all grid points other than the grid point which contains the modal parameters of the system. The parametric approach uses the state space model and properties of the controllability matrix to obtain the state transition matrix which contains all modal information. We discuss and illustrate the benefits of the proposed algorithms using a numerical and two experimental tests and we conclude that the nonparametric approach is very time consuming when a large number of samples is considered and does not outperform the parametric approach. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Modal parameters iterative algorithm State space model Controllability matrix Transition matrix

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A generalized descriptor-system robust H_∞ control of autonomous microgrids to improve small and large signal stability considering communication delays and load nonlinearities

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2017年 92卷 63-82页

作者： Baghaee, Hamid Reza Mirsalim, Mojtaba Gharehpetian, Gevork B. Talebi, Heidar Ali Amirkabir Univ Technol Elect Engn Dept Tehran Iran

This paper presents a descriptor system H-infinity approach to enhance performance of robust Hos controller and previously-reported decentralized robust servo-mechanism (DRSM) control scheme for autonomous voltage sourced converter (VSC)-based microgrids including multiple distributed energy resources (DERs). The power management system specifies voltage set points for local controllers and the frequency of each DER unit is specified by a hierarchical droop-based control structure. A descriptor system liso robust controller is designed based on a closed-loop representation of microgrid either with H-infinity or DRSM controller for set point tracking, disturbance rejection and improving performance of microgrid for small/large-signal disturbances and nonlinear loads. Here, unlike some of the previous researches, the load current is modeled as disturbance and also communication time-delay is considered. The theoretical concepts of proposed control strategy, including mathematical modeling of microgrid, basic theorems, and design procedure are outlines. Then, design problem is formulated by a set of linear/bilinear matrix inequalities and then solved using a new iterative algorithm in the form of convex optimization problem. To demonstrate effectiveness of the proposed control scheme, offline time-domain simulation studies are performed on a multi-DER microgrid in MATLAB/Simulink environment and also the results are experimentally verified by OPAL-RT real time digital simulator. (C) 2017 Published by Elsevier Ltd.

关键词： Microgrid Descriptor-system robust H-infinity control Distributed energy resources Linear matrix inequality Time-delay systems iterative algorithm Stability

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Augmented Lagrangian alternating direction method for low-rank minimization via non-convex approximation

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SIGNAL IMAGE AND VIDEO PROCESSING 2017年第7期11卷 1271-1278页

作者： Chen, Yongyong Wang, Yongli Li, Mingqiang He, Guoping Shandong Univ Sci & Technol Coll Math & Syst Sci Qingdao 266590 Peoples R China Univ Chinese Acad Sci Sch Math Sci Beijing 100049 Peoples R China Shandong Acad Sci Jinan 250014 Shandong Peoples R China

This paper concerns the low-rank minimization problems which consist of finding a matrix of minimum rank subject to linear constraints. Many existing approaches, which used the nuclear norm as a convex surrogate of the rank function, usually result in a suboptimal solution. To seek a tighter rank approximation, we develop a non-convex surrogate to approximate the rank function based on the Laplace function. An iterative algorithm based on the augmented Lagrangian multipliers method is developed. Empirical studies for practical applications including robust principal component analysis and low-rank representation demonstrate that our proposed algorithm outperforms many other state-of-the-art convex and non-convex methods developed recently in the literature.

关键词： Low-rank minimization Non-convex approximation iterative algorithm Difference of convex programming

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A new approach of extracting vegetation points from urban airborne LiDAR data

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Global Geology 2018年第3期21卷 194-202页

作者： CUI Shaochen YANG Yuanxin YANG Guodong ZHANG Xuqing College of Geo-Exploration Science and Technology Jilin University Air Force Academy Institute of Engineering Design

Urban vegetation has been an important indicator for the evaluation of eco-cities, which is of great significance to promote eeo-city construction. We study and discuss the commonly used urban vegetation extrac-tion methods. The extraction of vegetation points in this study is completed through mathematical statistics, mean-square error, successive differences and iterative algorithm which are based on the analysis of different spatial morphological characteristics in urban point clouds. Linyi, a city of Shandong Province in China, is se-lected as the study area to test this method and the result shows that the proposed method has a strong practicali- ty in urban vegetation point cloud extraction. Only 3D coordinate properties of the LiDAR point clouds are used in this method and it does not require additional information, for instance, return intensity, which makes the method more applicable and operable.

关键词： airborne LiDAR urban vegetation points two-dimensional grid mesh mean-square error successive differences iterative algorithm

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Backtracking-based matching pursuit method for distributed compressed sensing

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MULTIMEDIA TOOLS AND APPLICATIONS 2017年第13期76卷 14691-14710页

作者： Zhang, Yujie Qi, Rui Zeng, Yanni China Univ Geosci Sch Math & Phys Wuhan Peoples R China Univ Windsor Sch Comp Sci Windsor ON Canada Naval Univ Engn Sch Sci Wuhan Peoples R China Hubei Univ Econ Fac Stat Wuhan Peoples R China

In this paper, we study a distributed compressed sensing (DCS) problem in which we need to recover a set of jointly sparse vectors from the measurements. A Backtracking-based Adaptive Orthogonal Matching Pursuit (BAOMP) method to approximately sparse solutions for DCS is proposed. It is an iterative approach where each iteration consists of consecutive forward selection to adaptively choose several atoms and backward removal stages to detect the previous chosen atoms' reliability and then delete the unreliable atoms at each iteration. Also, unlike its several predecessors, the proposed method does not require the sparsity level to be known as a prior which makes it a potential candidate for many practical applications, when the sparsity of signals is not available. We demonstrate the reconstruction ability of the proposed algorithm on both synthetically generated data and image using Normal and Binary sparse signals, and the real-life electrocardiography (ECG) data, where the proposed method yields less reconstruction error and higher exact recovery rate than other existing DCS algorithms.

关键词： Distributed compressed sensing Greedy algorithm Sparse signal reconstruction iterative algorithm Orthogonal matching pursuit

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New Word Extraction From Chinese Financial Documents

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IEEE SIGNAL PROCESSING LETTERS 2017年第6期24卷 770-773页

作者： Yan, Liwei Bai, Bo Chen, Wei Wu, Dapeng Oliver Tsinghua Univ Dept Elect Engn Tsinghua Natl Lab Informat Sci & Technol Beijing 100084 Peoples R China Huawei Technol Co Ltd Future Network Theory Lab Shatin Hong Kong Peoples R China Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA

With the tremendous development of data science, using unstructured documents to analyze marketing dynamics is attracting a great deal of attention. In this letter, we propose an iterative scheme to extract the new words, which is often a bottleneck for Chinese natural language processing (NLP) in financial markets analysis. In contrast to existing static features, the key novelty is the proposed dynamic features that characterize the similarity of context patterns. Via iteration, distinguishable seed context patterns are extracted. Tested on a 203 MB corpus, 19 291 words representing emerging industries, entities, projects, and products were extracted with a precision of 89.8% and recall of 88.9%, which outperforms most competitor methods.

关键词： Chinese new word extraction iterative algorithm natural language processing static/dynamic features support vector machine

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Pore network modeling of phase change in PEM fuel cell fibrous cathode

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JOURNAL OF APPLIED ELECTROCHEMISTRY 2017年第12期47卷 1323-1338页

作者： Aghighi, Mahmoudreza Gostick, Jeff McGill Univ Dept Chem Engn Montreal PQ Canada

A pore network model has been applied to the cathode side of a fuel cell membrane electrode assembly to investigate the mechanisms leading to liquid water formation in the cell. This model includes mass diffusion, liquid water percolation, thermal and electrical conduction to model phase change which is highly dependent on the local morphology of the cathode side. An iterative algorithm was developed to simulate transport processes within the cathode side of PEMFC applying a pseudo-transient pore network model at constant voltage boundary condition. This algorithm represents a significant improvement over previous pore network models that only considered capillary invasion of water from the catalyst layer and provides useful insights into the mechanism of water transport in the electrodes, especially condensation and evaporation. The electrochemical performance of PEMFCs was simulated under different relative humidity conditions to study the effect of water phase change on the cell performance. This model highlights the ability of pore network models to resolve the discrete water clusters in the electrodes which is essential to the two-phase transport behavior especially the transport of water vapor to and from condensed water clusters.

关键词： Pore network model PEM fuel cell Phase change iterative algorithm Relative humidity

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