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2015年全国微波毫米波会议

作者： Xin Fu Li Jun Jiang Hong Tat Ewe Department of Electrical and Electronic Engineering The University of Hong Kong Department of Internet Engineering and Computer Science Universiti Tunku Abdul Rahman

A new hierarchical algorithm based on surface equivalence principle is applied to volume integral equation in this work. The equivalent sources residing on relaxed spherical equivalence surfaces are established by closed-form integral operators rather than numerical approximations. Consequently, it is straightforward to implement a hierarchical algorithm. Numerical examples validate the accuracy and capability of the proposed algorithm.

关键词： Volume integral equation hierarchical algorithm equivalent sources electromagnetic scattering

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hierarchical linear and nonlinear adaptive learning model for system identification and prediction

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APPLIED INTELLIGENCE 2020年第6期50卷 1699-1710页

作者： Abu Jami'in, Mohammad Anam, Khairul Rulaningtyas, Riries Mudjiono, Urip Adianto, Adianto Wee, Hui-Ming Politekn Perkapalan Negeri Surabaya Jalan Tekn Kimia Kampus ITS Sukolilo Surabaya Surabaya 60111 Indonesia Jember Univ UNEJ Jember Indonesia Airlangga Univ UNAIR Surabaya Indonesia Chung Yuan Christian Univ Taoyuan Taiwan

In this paper, we propose a method to increase the model accuracy with linear and nonlinear sub-models. The linear sub-model applies the least square error (LSE) algorithm and the nonlinear sub-model uses neural networks (NN). The two sub-models are updated hierarchically using the Lyapunov function. The proposed method has two advantages: 1) The neural networks is a multi-parametric model. Using the proposed model, the weights of NN model can be summarized into the coefficients or parameters of auto-regressive eXogenous/auto-regressive moving average (ARX/ARMA) model structure, making it easier to establish control laws, 2) learning rate is updated to ensure the convergence of errors at each training epoch. One can improve the accuracy of model and the whole control system. We have demonstrated by the experimental studies that the proposed technique gives better results when compared to the existing studies.

关键词： System identification hierarchical algorithm Adaptive learning Prediction Parameter estimation

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Parameter convergence in nonlinearly parameterized systems

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2003年第3期48卷 397-412页

作者： Cao, CY Annaswamy, AM Kojic, A MIT Dept Mech Engn Act Adapt Control Lab Cambridge MA 02139 USA Robert Bosch Corp Palo Alto CA 94130 USA

A large class of problems in parameter estimation concerns nonlinearly parametrized systems. Over the past few years, a stability framework for estimation and control of such systems has been established. We address the issue of parameter convergence in such systems in this paper. Systems with both convex/concave and general parameterizations are considered. In the former case, sufficient conditions are derived under which parameter estimates converge to their true values using a min-max algorithm as in a previous. work by Armaswamy et al. In the latter case, to achieve parameter convergence a hierarchical min-max algorithm is proposed where the lower level consists of a min-max algorithm and the higher level component updates the bounds on the parameter region within which the unknown parameter is known to lie. Using this hierarchical algorithm, a necessary and sufficient condition is established for global parameter convergence in systems with a general nonlinear parameterization. In both cases, the conditions needed are shown to be stronger than linear persistent excitation conditions that guarantee parameter convergence in linearly parametrized systems. Explanations and examples of these conditions and simulation results are included to illustrate the nature of these conditions. A general definition of nonlinear persistent excitation that leads. to parameter convergence is proposed at the end of this paper.

关键词： convex persistent excitation convex/concave parameterization hierarchical algorithm nonlinear parameterization nonlinear persistent excitation parameter convergence parameter estimation

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ROUTING IN MULTIDOMAIN NETWORKS

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IEEE-ACM TRANSACTIONS ON NETWORKING 1994年第3期2卷 252-262页

作者： DIMITRIJEVIC, DD MAGLARIS, B BOORSTYN, RR CONTEL TECHNOL CTR CHANTILLY VA USA NATL TECH UNIV ATHENS DEPT ELECT & COMP ENGN GR-15773 ATHENS GREECE POLYTECH INST NEW YORK BROOKLYN NY 11201 USA

We investigate the problem of management and control in a large and, for simplicity, homogeneous packet-switched network. Specifically we focus on routing, an important function of network management. The network consists of several individually controlled domains. Domains are interconnected via gateway links. Each domain is controlled by its own Network Control Center, while the overall network performance is managed by an Integrated Network Control Center. Each Center has only a portion of the information required for global routing. We investigate the impact of the reduced information available at each center on network performance (average delay in our case). We present a general approach to designing a hierarchical algorithm for routing in multidomain networks. We propose a heuristic procedure suitable for packet-switched networks. Several numerical examples will illustrate the impact of incomplete information on the network. Performance is compared with a lower bound obtained, which is not differentiating destinations in other domains. Therefore, for this bound, each domain is perceived as a single node in a simplified model of the network.

关键词： Telecommunication Network Routing Telecommunication Network Management Delays Packet Switching Telecommunications Control Network Topology Multidomain Networks Management Control Homogeneous Packet Switched Network Routing Gateway Links Domain Network Control Center Network Performance Integrated Network Control Center Reduced Information Delay hierarchical algorithm Heuristic Procedure Routing Intelligent Networks Communication System Control Computer Networks algorithm Design And Analysis Delay Communication Networks Control Systems Peer To Peer Computing Packet Switching

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Biogascluster: A clustering algorithm to identify potential partnerships between agribusiness properties

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RENEWABLE ENERGY 2023年第1期206卷 982-993页

作者： Obal, Thalita Monteiro de Souza, Jovani Taveira de Jesus, Romulo Henrique Gomes de Francisco, Antonio Carlos Univ Tecnol Fed Parana UTFPR Postgrad Program Prod Engn PPGEP Sustainable Prod Syst Lab LESP R Doutor Washington Subtil Chueire330 BR-84017220 Ponta Grossa Parana Brazil R Doutor Washington Subtil Chueire 330 BR-84017220 Ponta Grossa Parana Brazil

The lack of partnerships between biomass generating producers is one of the main barriers to efficient biogas production. Partnerships can help producers properly dispose of waste, assist in the supply of biodigesters, allow the union of properties with different potential biomass generators into clusters, and optimize operating costs. In this sense, new measures must be adopted with regard to the establishment of strategic partnerships between producers. Therefore, in this paper, we propose a new clustering algorithm, BiogasCluster, to decide the optimal number of clusters for generating a renewable energy community. To test the proposed algorithm's applicability, we implemented the algorithm in R language. Experiments with real databases showed that the BiogasCluster proved to be efficient in generating stable clusters for all considered scenarios. It was also found that the filters and criteria used in the proposed algorithm have not been used in previous studies. This study provides important guidance to creating strategic partnerships within bioenergy generation in addition to obtaining a preliminary assessment of the possibility of establishing clusters of rural properties with the aim of achieving energy security and adding value to their businesses.

关键词： Partnerships Biogas Clustering hierarchical algorithm Renewable energy

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Exploiting homogeneity in protein sequence clusters for construction of protein family hierarchies

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PATTERN RECOGNITION 2006年第12期39卷 2356-2369页

作者： Chen, Chien-Yu Chung, Wen-Chin Su, Chung-Tsai Natl Taiwan Univ Dept Bioind Mechatron Engn Taipei 106 Taiwan Natl Taiwan Univ Dept Comp Sci & Informat Engn Taipei 106 Taiwan

In the field of proteomics, protein hierarchies based on sequence analysis have been extensively applied to automate the annotations of new proteins and facilitate the discovery and analysis of protein families. However, the presence of ambiguous similarities in large databases increases the difficulty of delivering protein family hierarchies with favorable sensitivity and specificity. This work develops the HomoClust algorithm that exploits the homogeneity of protein sequences in generating protein family hierarchies. HomoClust improves the clustering quality of traditional hierarchical clustering algorithms by adopting different clustering mechanisms for different levels of sequence similarity. With considering homogeneity detection during clustering process, HomoClust increases the sensitivity of protein clusters without a drop in high specificity. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.

关键词： protein sequence clustering family analysis twilight zone hierarchical algorithm

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ADMM-Based Coordination of Electric Vehicles in Constrained Distribution Networks Considering Fast Charging and Degradation

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2021年第1期22卷 565-578页

作者： Zhou, Xu Zou, Suli Wang, Peng Ma, Zhongjing Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China Tsinghua Univ Dept Elect Engn State Key Lab Power Syst Beijing 100084 Peoples R China

Acting as a key to future environmentally friendly transportation systems, electric vehicles (EVs) have attached importance to develop fast charging technologies to accomplish the requirement of vehicle users. However, fast charging behaviors would cause degradations in EVs' batteries, as well as negative effects like new demand peak and feeder overloads to the connected distribution network, especially when plugging in large scale EVs. Decentralized coordination is encouraged and our goal is to achieve an optimal strategy profile for EVs in a decentralized way considering both the need of fast charging and reducing degradations in batteries and the distribution network. In this article, we innovatively model the EV fast charging problem as an optimization coordination problem subject to the coupled feeder capacity constraints in the distribution network. The need of fast charging is expressed by the total charging time, and the relative tendency to fully charge within the desired time period. We introduce a l(0) -norm of the charging strategy which is non-convex to represent the total charging time, and apply the l(1)-norm minimization to approximate the sparse solution of l(0)-norm minimization. The shorter the charging horizon is the stronger willing of fast charging the user has. The objective of the optimization problem tradeoffs the EVs' battery degradation cost, the load regulation in the distribution network, the satisfaction of charging and the total charging time, which is non-separable among individual charging behaviors. Even though alternating direction method of multipliers (ADMM) has been widely applied in distributed optimization with separable objective and coupled constraints, its decentralized scheme cannot be applied directly to the underlying non-separable EV charging coordination problem. Hence, a hierarchical algorithm based on ADMM is proposed such that the convergence to the optimal strategies is guaranteed under certain step-size parameter.

关键词： Electric vehicles constrained distribution network fast charging non-separable objective alternating direction method of multipliers gradient projection hierarchical algorithm convergence

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Real-time system identification using hierarchical interhealing model classes

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STRUCTURAL CONTROL & HEALTH MONITORING 2020年第12期27卷 e2628-e2628页

作者： Yuen, Ka-Veng Dong, Le Univ Macau State Key Lab Internet Things Smart City Macau Peoples R China Univ Macau Dept Civil & Environm Engn Macau Peoples R China

In this article, a novel algorithm is proposed for real-time system identification using hierarchical interhealing model classes. One major difficulty in the system identification for large structures is to determine the complexity of the structural model and the number of unknown parameters. One can detect finer damages with more unknown stiffness parameters, but this may cause fluctuating or even unidentifiable results. Although Bayesian model class selection allows one to choose among some prescribed model classes, the number of possible model classes for large structures is huge. In this paper, we propose a new method using hierarchical interhealing model classes. The modeling errors of these model classes can be corrected adaptively according to the data and the results from the optimal model class. This includes not only the errors in the parameters but also the deficiencies of the parametric models. Furthermore, the model classes are established in a hierarchical manner so that the proposed strategy requires only a small number of model classes, yet being able to explore a large solution space. Consequently, the proposed algorithm can handle a large number of damage possibilities while it maintains relatively low computational cost. Two examples are presented, and the results show that the proposed algorithm can detect, locate, and quantify damages reliably and efficiently.

关键词： Bayesian inference extended Kalman filter hierarchical algorithm interhealing real-time structural health monitoring

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DIAGNOSING ARBITRARILY CONNECTED PARALLEL COMPUTERS WITH HIGH PROBABILITY

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IEEE TRANSACTIONS ON COMPUTERS 1992年第5期41卷 606-615页

作者： RANGARAJAN, S FUSSELL, D UNIV TEXAS DEPT COMP SCIAUSTINTX 78712

Previous work on system-level fault diagnosis has largely been based on the PMC model [10]. Recent work has extended the original deterministic PMC model to allow more realistic probabilistic diagnosis. Recently [14], [1], algorithms were presented for systems of N processors which require each processor to be tested by O(log N) neighboring processors (testers) to achieve a probability of correct diagnosis approaching one as N --> infinity. These results are applicable to hypercube systems, but many real multiprocessor systems do not satisfy this connectivity requirement. In this paper we first present an algorithm in which a constant number of processors each perform O(log N) tests on any given processor and the probability of correct diagnosis approaches one as N --> infinity. We further present a hierarchical testing algorithm and show that asymptotically efficient testing can be done when the product of number of testers x number of tests each tester performs on a processor grows as O(log N) as N --> infinity. Our hierarchical algorithm allows the number of tests each tester must perform to be adjusted as per the requirements of the topology.

关键词： ASYMPTOTICALLY HIGH PROBABILITY hierarchical algorithm PROBABILISTIC DIAGNOSIS SYSTEM-LEVEL DIAGNOSIS TEST TESTER OVERHEAD

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Topology preserving top-down compression of 2D vector fields using bintree and triangular quadtrees

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2003年第4期9卷 433-442页

作者： Lodha, SK Faaland, NM Renteria, JC Univ Calif Santa Cruz Dept Comp Sci Santa Cruz CA 95064 USA Army Res Lab Aberdeen MD USA

We present a hierarchical top-down refinement algorithm for compressing 2D vector fields that preserves topology. Our approach is to reconstruct the data set using adaptive refinement that considers topology. The algorithms start with little data and subdivide regions that are most likely to reconstruct the original topology of the given data set. We use two different refinement techniques. The first technique uses bintree subdivision and linear interpolation. The second algorithm is driven by triangular quadtree subdivision with Coons patch quadratic interpolation. We employ local error metrics to measure the quality of compression and as a global metric we compute Earth Mover's Distance (EMD) to measure the deviation from the original topology. Experiments with both analytic and simulated data sets are presented. Results indicate that one can obtain significant compression with low errors without losing topological information. Advantages and disadvantages of different topology preserving compression algorithms are also discussed in the paper.

关键词： vector fields compression topology top-down bintree quadtree hierarchical algorithm

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