We introduce ASAP2, an improved variant of the batch-means algorithm ASAP for steady-state simulation output analysis. ASAP2 operates as follows: the batch size is progressively increased until the batch means pass th...
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We introduce ASAP2, an improved variant of the batch-means algorithm ASAP for steady-state simulation output analysis. ASAP2 operates as follows: the batch size is progressively increased until the batch means pass the Shapiro-Wilk test for multivariate normality; and then ASAP2 delivers a correlation-adjusted confidence interval. The latter adjustment is based on an inverted Cornish-Fisher expansion for the classical batch means t-ratio, where the terms of the expansion are estimated via a first-order autoregressive time series model of the batch means. ASAP2 is a sequential procedure designed to deliver a confidence interval that satisfies a prespecified absolute or relative precision requirement. When used in this way, ASAP2 compares favorably to ASAP and the well-known procedures ABATCH and LBATCH with respect to close conformance to the precision requirement as well as coverage probability and mean and variance of the half-length of the final confidence interval.
This paper aims at proposing and comparing two fuzzy models and a statistical model for clustering based on L1-space. Clustering methods in the fuzzy models are the standard fuzzy c-means and an entropy regularization...
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Introduction Polymers exhibit larger elongation and more significant rate- and time-dependent behavior at higher temperature [1]. To understand properties of polymer matrix composites and to correctly evaluate their p...
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Introduction Polymers exhibit larger elongation and more significant rate- and time-dependent behavior at higher temperature [1]. To understand properties of polymer matrix composites and to correctly evaluate their performance characteristics, therefore, it is one of the most important issues to elucidate the time- and rate-dependent nonlinear behavior of polymer matrix composites at elevated temperature. The objective of the present study is to elucidate characteristics of the short-term stress relaxation behavior of angle-ply CFRP laminates at high temperature. The stress relaxation curves for various angle-ply laminates are presented. By the normalization with respect to the maximum stress at the beginning of each relaxation test, we obtain a master relaxation curve that is characterized by the off-axis time-dependent response of constituent unidirectional plies.
This paper addresses the problem of robust /spl Hscr//sub /spl infin// filtering for linear discrete-time systems subject to parameter uncertainties in the system state-space model and with multiple time delays in the...
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This paper addresses the problem of robust /spl Hscr//sub /spl infin// filtering for linear discrete-time systems subject to parameter uncertainties in the system state-space model and with multiple time delays in the state variables. The uncertain parameters are supposed to belong to a given convex bounded polyhedral domain. A methodology is developed to design a stable linear filter that assures asymptotic stability and a prescribed /spl Hscr//sub /spl infin// performance for the filtering error, irrespective of the uncertainty and the time delays. The proposed design is given in terms of linear matrix inequalities, which has the advantage in that it can be implemented numerically very efficiently.
We present the fuzzy Bayes predictor (FBP), a hybrid system for the task of monthly electric load forecasting. The FBP is a modification we introduce in the naive Bayes classifier in order to enable it to predict nume...
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ISBN:
(纸本)0780370449
We present the fuzzy Bayes predictor (FBP), a hybrid system for the task of monthly electric load forecasting. The FBP is a modification we introduce in the naive Bayes classifier in order to enable it to predict numerical values. We consider three versions of the FBP, each one with a different dependence among the input data: independence, first-order and second-order dependence. For verifying the efficiency of the FBP's prediction, we compare it with two fuzzy systems and two traditional forecasting methods, Box-Jenkins and Winters exponential smoothing.
In this paper we present our computational experience with a heuristic for the problem of minimizing fuel cost on steady-state gas transmission problems on cyclic networks. The procedure is based on a two-stage iterat...
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In this paper we present our computational experience with a heuristic for the problem of minimizing fuel cost on steady-state gas transmission problems on cyclic networks. The procedure is based on a two-stage iterative procedure, where, in a given iteration, gas flow variables are fixed and optimal pressure variables are found via dynamic programming in the first stage. In the second stage, the pressure variables are fixed and an attempt is made to find a set of flow variables that improve the objective function by exploiting the underlying network structure. This work focuses on cyclic network topologies, that is, networks with at least one cycle containing two or more compressor stations. This kind of topologies posses the highest degree of difficulty in real-world problems.
The problem of robust H/spl infin/ filtering for continuous-time uncertain linear systems with multiple time-varying delays in the state variables is investigated. The uncertain parameters are supposed to belong to a ...
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The problem of robust H/spl infin/ filtering for continuous-time uncertain linear systems with multiple time-varying delays in the state variables is investigated. The uncertain parameters are supposed to belong to a given convex bounded polyhedral domain. The aim is to design a stable linear filter assuring asymptotic stability and a prescribed H/spl infin/ performance level for the filtering error system, irrespective of the uncertainties and the time delays. Sufficient conditions for the existence of such a filter are established in terms of linear matrix inequalities, which can be efficiently solved by means of powerful convex programming tools with global convergence assured. An example illustrates the proposed methodology.
The problem of robust H∞ state-feedback control design for a class of continuous-time linear systems with Markovian jumping parameters and multiple time-varying delays at the states, and subject to uncertain paramete...
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The problem of robust H ∞ state-feedback control design for a class of continuous-time linear systems with Markovian jumping parameters and multiple time-varying delays at the states, and subject to uncertain parame...
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The problem of robust H ∞ state-feedback control design for a class of continuous-time linear systems with Markovian jumping parameters and multiple time-varying delays at the states, and subject to uncertain parameters is addressed in this paper. It is assumed that the jumping parameters are available and the uncertain parameter belong to given convex bounded domains (polytope type uncertainty). A delay-independent sufficient condition assuring robust mean square stability and a prescribed level of H ∞ disturbance attenuation for the closed-loop system is established in terms of linear matrix inequalities.
This paper addresses the problem of robust H ∞ state-feedback control design for uncertain discrete-time linear systems with multiple time delays at the states and Markovian jumping parameters. The jumping parameters...
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This paper addresses the problem of robust H ∞ state-feedback control design for uncertain discrete-time linear systems with multiple time delays at the states and Markovian jumping parameters. The jumping parameters are assumed to be available and the uncertainties are supposed to belong to convex bounded domains (polytope type uncertainty). Delay-independent sufficient conditions assuring robust stochastic stability and a prescribed H ∞ disturbance attenuation for the closed-loop uncertain discrete-time linear system with multiple time delays and Markovian jumping parameters are established in terms of linear matrix inequalities, which have the advantage that can be implemented numerically veryefficiently.
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