Results 271 to 280 of about 7,569,463 (308)
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Optimization of CSTRs in series by dynamic programming
Biotechnology and Bioengineering, 1986AbstractThis article concerns the development of a simple yet effective procedure for optimizing the design of a reactor system employing CSTRs in series. The basic approach used in this work was to translate the problem of reactor design to a mathematical programming model. The resulting model was then solved by dynamic programming.
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Fluctuation Dynamics in Electroencephalogram Time Series
2005We investigated the characterization of the complexity of electroencephalogram (EEG) fluctuations by monofractals and multifractals. We used EEG time series taken from normal, healthy subjects with their eyes open and their eyes closed, and from patients during epileptic seizures.
In-Ho Song, Doo-Soo Lee
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Dynamical SVM for Time Series Classification
2012We present a method for classifying multidimensional time series using concepts from nonlinear dynamical systems theory. Our contribution is an extension of support vector machines (SVM) that controls a nonlinear dynamical system. We use a chain of coupled Rossler oscillators with diffusive coupling to model highly nonlinear and chaotic time series ...
Ramón Huerta +3 more
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Dynamic Symbolization of Streaming Time Series
2004Symbolization of time series is an important preprocessing subroutine for many data mining tasks. However, it is usually difficult, if not impossible, to apply the traditional static symbolization approach on streaming time series, because of either the low efficiency of re-computing the typical sub-series, or the low capability of representing the up ...
Xiaoming Jin +2 more
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Minimum cost dynamic flows: The series-parallel case
Networks, 1995AbstractA dynamic network consists of a directed graph with capacities, costs, and integral transit times on the arcs. In the minimum‐cost dynamic flow problem (MCDFP), the goal is to compute, for a given dynamic network with source s, sink t, and two integers v and T, a feasible dynamic flow from s to t of value v, obeying the time bound T, and having
Klinz, Bettina, Woeginger, Gerhard
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Time Series and Dynamic Models
2004Abstract This chapter treats the modelling of variables that are observed sequentially over time. The main focus is on univariate time series models for a single economic variable, but we also discuss regression models with lags and multivariate time series models.
Christiaan Heij +4 more
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Random dynamical models from time series
Physical Review E, 2012In this work we formulate a consistent Bayesian approach to modeling stochastic (random) dynamical systems by time series and implement it by means of artificial neural networks. The feasibility of this approach for both creating models adequately reproducing the observed stationary regime of system evolution, and predicting changes in qualitative ...
Y I, Molkov +3 more
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Time Series and Dynamic Models
1996In this book Christian Gourieroux and Alain Monfort provide an up-to-date and comprehensive analysis of modern time series econometrics. They have succeeded in synthesising in an organised and integrated way a broad and diverse literature. While the book does not assume a deep knowledge of economics, one of its most attractive features is the close ...
Christian Gourieroux, Alain Monfort
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Dynamic Simulator for Thyristor Controlled Series Capacitor
2008 IEEE Industry Applications Society Annual Meeting, 2008This paper presents an alternative approach to thyristor controlled series capacitor (TCSC) performance analysis. The approach is to interface a small-scale physical model of the TCSC with a classic physical power system simulation laboratory. The platform is capable to investigate the operation, protection, and control strategies of TCSCs. Furthermore,
Kejun Li, Jianguo Zhao, Wei-Jen Lee
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2004
Abstract This chapter presents the finite sample analysis of the time series models used in economics and finance. It considers the autoregressive model (AR), AR with regressors, and autoregressive moving average models with regressors. The exact and approximate moments, as well as distributions of the estimators of the lag coefficients ...
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Abstract This chapter presents the finite sample analysis of the time series models used in economics and finance. It considers the autoregressive model (AR), AR with regressors, and autoregressive moving average models with regressors. The exact and approximate moments, as well as distributions of the estimators of the lag coefficients ...
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