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Proposed Algorithms (proposed + algorithms)
Selected AbstractsNovel coupling Rosenbrock-based algorithms for real-time dynamic substructure testingEARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 3 2008O. S. Bursi Abstract Real-time testing with dynamic substructuring is a novel experimental technique capable of assessing the behaviour of structures subjected to dynamic loadings including earthquakes. The technique involves recreating the dynamics of the entire structure by combining an experimental test piece consisting of part of the structure with a numerical model simulating the remainder of the structure. These substructures interact in real time to emulate the behaviour of the entire structure. Time integration is the most versatile method for analysing the general case of linear and non-linear semi-discretized equations of motion. In this paper we propose for substructure testing, L-stable real-time (LSRT) compatible integrators with two and three stages derived from the Rosenbrock methods. These algorithms are unconditionally stable for uncoupled problems and entail a moderate computational cost for real-time performance. They can also effectively deal with stiff problems, i.e. complex emulated structures for which solutions can change on a time scale that is very short compared with the interval of time integration, but where the solution of interest changes on a much longer time scale. Stability conditions of the coupled substructures are analysed by means of the zero-stability approach, and the accuracy of the novel algorithms in the coupled case is assessed in both the unforced and forced conditions. LSRT algorithms are shown to be more competitive than popular Runge,Kutta methods in terms of stability, accuracy and ease of implementation. Numerical simulations and real-time substructure tests are used to demonstrate the favourable properties of the proposed algorithms. Copyright © 2007 John Wiley & Sons, Ltd. [source] Coupling BEM/TBEM and MFS for the simulation of transient conduction heat transferINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 2 2010António Tadeu Abstract The coupling between the boundary element method (BEM)/the traction boundary element method (TBEM) and the method of fundamental solutions (MFS) is proposed for the transient analysis of conduction heat transfer in the presence of inclusions, thereby overcoming the limitations posed by each method. The full domain is divided into sub-domains, which are modeled using the BEM/TBEM and the MFS, and the coupling of the sub-domains is achieved by imposing the required boundary conditions. The accuracy of the proposed algorithms, using different combinations of BEM/TBEM and MFS formulations, is checked by comparing the resulting solutions against referenced solutions. The applicability of the proposed methodology is shown by simulating the thermal behavior of a solid ring incorporating a crack or a thin inclusion in its wall. The crack is assumed to have null thickness and does not allow diffusion of energy; hence, the heat fluxes are null along its boundary. The thin inclusion is modeled as filled with thermal insulating material. Copyright © 2010 John Wiley & Sons, Ltd. [source] Asymptotic numerical methods for unilateral contactINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 6 2006W. Aggoune Abstract New algorithms based upon the asymptotic numerical method (ANM) are proposed to solve unilateral contact problems. ANM leads to a representation of a solution path in terms of series or Padé approximants. To get a smooth solution path, a hyperbolic relation between contact forces and clearance is introduced. Three key points are discussed: the influence of the regularization of the contact law, the discretization of the contact force by Lagrange multipliers and prediction,correction algorithms. Simple benchmarks are considered to evaluate the relevance of the proposed algorithms. Copyright © 2006 John Wiley & Sons, Ltd. [source] Identification of dual-rate systems based on finite impulse response modelsINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 7 2004Feng Ding Abstract Two identification algorithms, a least squares and a correlation analysis based, are developed for dual-rate stochastic systems in which the output sampling period is an integer multiple of the input updating period. The basic idea is to use auxiliary FIR models to predict unmeasurable noise-free (true) outputs, and then use these and system inputs to identify parameters of underlying fast single-rate models. The simulation results indicate that the proposed algorithms are effective. Copyright © 2004 John Wiley & Sons, Ltd. [source] A fast second-order signal separation algorithms with on-line capabilitiesINTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, Issue 4 2002M. F. Fahmy In correlation-based signal separation algorithms, the received mixed signals are fed to a de-coupling system designed to minimize the output cross-correlation functions. If minimizaion is perfect, each of the system's outputs carries only one signal independent of the others. In these algorithms, the computation burden of the output cross-correlation functions normally slows down the separation algorithm. This paper, describes a computationally efficient method for off-line pre-computation of the needed cross-correlation functions. Explicit formulas have been derived for the output cross-correlation functions in terms of the received input signals and the de-coupling system parameters. Then, it is shown that signal separation amounts to the least-squares solution of a system of linear equations describing these output cross-correlation functions, evaluated over a batch of lags. Next, a fast RLS-type adaptive algorithm is devised for on-line signal separation. In this respect, an algorithm is derived for updating the de-coupling parameters as data comes in. This update is achieved recursively, along the negative of the steepest descent directions of an objective cost function describing the output cross-correlation functions over a batch of lags, subject to equal output power constraints. Illustrative examples are given to demonstrate the effectiveness of the proposed algorithms. Copyright © 2002 John Wiley & Sons, Ltd. [source] A utility-based capacity optimization framework for achieving cooperative diversity in the hierarchical converged heterogeneous wireless networksINTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, Issue 12 2008Mugen Peng Abstract A hierarchical convergence mechanism for the heterogeneous wireless communication system via the heterogeneous cooperative relay node is presented in this paper, in which the techniques of cooperative communication and wireless relay are utilized to improve performances of the individual user and the overall converged networks. In order to evaluate the benefits of the proposal, a utility-based capacity optimization framework for achieving the heterogeneous cooperative diversity gain is proposed. The heterogeneous cooperative capacity, relay selection and power allocation theoretical models are derived individually. The joint optimization model for relay selection and power allocation is presented as well. Owing to the computation complexity, the sub-optimal cooperative relay selection algorithm, the sub-optimal power allocation algorithm and the sub-optimal joint algorithm are determined to approach the maximum overall networks' spectrum efficiency. These proposed algorithms are designed in conformance to guarantee the equivalent transmission rates of the different wireless access networks. The simulation results demonstrate that the utility-based capacity model is available for the heterogeneous cooperative wireless communication system, and the proposed algorithms can improve performances by achieving the cooperative gain and taking full advantage of the cross-layer design. Copyright © 2008 John Wiley & Sons, Ltd. [source] Priority-based adaptive routing in NGEO satellite networksINTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, Issue 3 2007Ömer Korçak Abstract In a non-geostationary satellite constellation with inter satellite links (ISLs), there could be many shortest paths between two satellites in terms of hop count. An efficient routing algorithm should effectively use these paths in order to distribute traffic to ISLs in a balanced way and to improve the performance of the system. This paper presents and evaluates a novel priority-based adaptive shortest path routing (PAR) scheme in order to achieve this goal. PAR sets the path towards the destination in a distributed manner, using a priority mechanism depending on the past utilization and buffering information of the ISLs. Moreover, to avoid unnecessary splitting of a flow and to achieve better utilization of ISLs, enhanced PAR (ePAR) scheme is proposed. This paper evaluates performance of the proposed techniques by employing an extensive set of simulations. Furthermore, since there are a number of ePAR parameters that should be adjusted depending on the network and traffic characteristics, a detailed analysis of ePAR scheme is provided to form a framework for setting the parameters. This paper also includes a method for adaptation of the proposed algorithms to minimum-delay path routing. Copyright © 2006 John Wiley & Sons, Ltd. [source] Robust adaptive fuzzy semi-decentralized control for a class of large-scale nonlinear systems using input,output linearization conceptINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 1 2010H. Yousef Abstract Stable direct and indirect adaptive fuzzy controllers based on input,output linearization concept are presented for a class of interconnected nonlinear systems with unknown nonlinear subsystems and interconnections. The interconnected nonlinear systems are represented not only in the canonical forms as in Yousef et al. (Int. J. Robust Nonlinear Control 2006; 16: 687,708) but also in the general forms. Hybrid adaptive fuzzy robust tracking control schemes that are based on a combination of an H, tracking theory and fuzzy control design are developed. In the proposed control schemes, all the states and signals are bounded and an H, tracking control performance is guaranteed without imposing any constraints or assumptions about the interconnections. Extensive simulation on the tracking of a two-link rigid robot manipulator and a numerical example verify the effectiveness of the proposed algorithms. Copyright © 2009 John Wiley & Sons, Ltd. [source] Kalman filter-based adaptive control for networked systems with unknown parameters and randomly missing outputsINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 18 2009Y. Shi Abstract This paper investigates the problem of adaptive control for networked control systems with unknown model parameters and randomly missing outputs. In particular, for a system with the autoregressive model with exogenous input placed in a network environment, the randomly missing output feature is modeled as a Bernoulli process. Then, an output estimator is designed to online estimate the missing output measurements, and further a Kalman filter-based method is proposed for parameter estimation. Based on the estimated output and the available output, and the estimated model parameters, an adaptive control is designed to make the output track the desired signal. Convergence properties of the proposed algorithms are analyzed in detail. Simulation examples illustrate the effectiveness of the proposed method. Copyright © 2008 John Wiley & Sons, Ltd. [source] Approximate algorithms for the container loading problemINTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, Issue 6 2002M. Hifi In this paper we develop several algorithms for solving three,dimensional cutting/packing problems. We begin by proposing an adaptation of the approach proposed in Hifi and Ouafi (1997) for solving two,staged unconstrained two,dimensional cutting problems. We show how the algorithm can be polynomially solved for producing a constant approximation ratio. We then extend this algorithm for developing better approximate algorithms. By using hill,climbing strategies, we construct some heuristics which produce a good trade,off between the computational time and the solution quality. The performance of the proposed algorithms is evaluated on different problem instances of the literature, with different sizes and densities (a total of 144 problem instances). [source] Weighted hybrid clustering by combining text mining and bibliometrics on a large-scale journal databaseJOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, Issue 6 2010Xinhai Liu We propose a new hybrid clustering framework to incorporate text mining with bibliometrics in journal set analysis. The framework integrates two different approaches: clustering ensemble and kernel-fusion clustering. To improve the flexibility and the efficiency of processing large-scale data, we propose an information-based weighting scheme to leverage the effect of multiple data sources in hybrid clustering. Three different algorithms are extended by the proposed weighting scheme and they are employed on a large journal set retrieved from the Web of Science (WoS) database. The clustering performance of the proposed algorithms is systematically evaluated using multiple evaluation methods, and they were cross-compared with alternative methods. Experimental results demonstrate that the proposed weighted hybrid clustering strategy is superior to other methods in clustering performance and efficiency. The proposed approach also provides a more refined structural mapping of journal sets, which is useful for monitoring and detecting new trends in different scientific fields. [source] Robust l2,l, state feedback control for uncertain discrete-time switched systems with mode-dependent time-varying delays,ASIAN JOURNAL OF CONTROL, Issue 4 2010Guangdeng Zong Abstract This paper deals with the problem of robust l2,l, state feedback control for uncertain discrete-time switched systems with mode-dependent time-varying delays. Attention is focused on the design of a switched state feedback controller, which guarantees the asymptotical stability of the closed-loop system and reduces the effect of the disturbance input on the controlled output to a prescribed level for all admissible uncertainties. By resorting to a descriptor system approach, delay-dependent sufficient conditions are presented in terms of linear matrix inequalities (LMIs). A numerical example is provided to demonstrate the effectiveness of the proposed algorithms. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source] Nested effects models for learning signaling networks from perturbation dataBIOMETRICAL JOURNAL, Issue 2 2009Holger Fröhlich Abstract Targeted gene perturbations have become a major tool to gain insight into complex cellular processes. In combination with the measurement of downstream effects via DNA microarrays, this approach can be used to gain insight into signaling pathways. Nested Effects Models were first introduced by Markowetz et al. as a probabilistic method to reverse engineer signaling cascades based on the nested structure of downstream perturbation effects. The basic framework was substantially extended later on by Fröhlich et al., Markowetz et al., and Tresch and Markowetz. In this paper, we present a review of the complete methodology with a detailed comparison of so far proposed algorithms on a qualitative and quantitative level. As an application, we present results on estimating the signaling network between 13 genes in the ER-, pathway of human MCF-7 breast cancer cells. Comparison with the literature shows a substantial overlap. [source] Three-Dimensional Array-Based Group Testing AlgorithmsBIOMETRICS, Issue 3 2009Hae-Young Kim Summary We derive the operating characteristics of three-dimensional array-based testing algorithms for case identification in the presence of testing error. The operating characteristics investigated include efficiency (i.e., expected number of tests per specimen) and error rates (e.g., sensitivity, specificity, positive, and negative predictive values). The methods are illustrated by comparing the proposed algorithms with previously studied hierarchical and two-dimensional array algorithms for detecting recent HIV infections in North Carolina. Our results indicate that three-dimensional array-based algorithms can be more efficient and accurate than previously proposed algorithms in settings with test error and low prevalence. [source] | |||||||||||||