منابع مشابه
Modeling continuous processes from data.
Experimental and simulated time series are necessarily discretized in time. However, many real and artificial systems are more naturally modeled as continuous-time systems. This paper reviews the major techniques employed to estimate a continuous vector field from a finite discrete time series. We compare the performance of various methods on experimental and artificial time series and explore ...
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Modeling Discrete and Continuous Processes
by Magne Myrtveit Normally, we try to aggregate discreteness in System Dynamics (SD) models by making continuous flows. This is a good modeling practice, but in some cases discreteness may have a significant influence on system behavior (see note). Consequently, we need to model such discreteness to explore its impact on behavior. The System Dynamics (SD) technology was originally designed with...
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Models of industrial processes often contain discrete phenomena superimposed on the continuous system behavior. Simulation of batch processes, start-up and shutdown procedures, fault diagnosis and alarms fall under this category. Models for such processes require a mathematical theory for both its continuous and discrete state transitions. A key problem in hybrid simulation lies in the detectio...
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Inference from hospital patient records is difficult because data collection is done at arbitrary (not evenlyspaced) time intervals, and key clinical information is recorded only in unstructured form (as free text in doctors’ notes). We present remind, a framework for performing inference from patient records based upon continuous-time Markov models and Bayesian networks. We empirically justify...
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ژورنال
عنوان ژورنال: Physical Review E
سال: 2002
ISSN: 1063-651X,1095-3787
DOI: 10.1103/physreve.65.046704