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Regression modeling, time-series modeling, pattern recognition modeling and stochastic process modeling are tested to model the expected occupancy status and their performances are compared in terms of the degree of statistical approximation to actual occupancy.
Three different mechanisms have been tested to model the flame, with good agreement between calculated and experimental results.
The HSDBC algorithm has been tested to model and control nonlinear systems including flexible robot manipulator and a twin rotor system using a PD-like FLC [35, 37].
A supervised feedforward back-propagation neural network was then designed, trained and tested to model and predict water consumption from January 1980 to December 1999.
A model was proposed and tested to model the dependence of quantum yield on photon energy and, thus, to estimate the band gap of the layers for both anodized Ta and Ta-19at% Al.
Increasing degrees of polynomials were tested to model the random permanent environment and genetic terms, and assessed by changes in the log likelihood.
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Seven models were tested to determine model fit to the data.
Finally, further investigation into the robustness of each statistical test to model misspecification would be of practical interest.
Higher ER values indicate higher likelihoods of the tested model relative to model b (e.g., the null model).
Some characterization test results to model parameters identification are included.
The credit crunch tested the model to destruction.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com