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Neural network (NN) approaches have been widely applied for modeling and identification of nonlinear multiple-input multiple-output (MIMO) systems.
This paper concerns on the aluminum foam material modeling and identification of constitutive parameters at high strain rates.
In the last few years, fractional calculus has been applied successfully in various areas to modify many existing models of physical processes, e.g., chemistry, biology, modeling and identification, electronics, wave propagation, and viscoelasticity (Rossikhin and Shitikova 1967; Bagley and Torvik 1986).
Based on the mathematical model of the aerial vehicle acquired by modeling and identification, a design for the structural parameters of the attitude control system is carried out, and the results of the attitude control flaps are verified by simulation experiments and flight tests of the aerial vehicle.
To reach the most economical process configuration, the superstructure model has been developed including binary interaction parameter regression of the NRTL-RK thermodynamic model, unit operation modeling, and identification of the connectivity of each of the unit operations in the superstructure.
IRMA is a synthetic network constructed in yeast and proposed as a benchmark for modeling and identification approaches (Cantone et al., 2009).
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This paper describes an interactive tool focused on teaching and learning basic concepts about modelling and identification.
Mechanical design, dynamics modeling, and system identification of the surgical robot are conducted.
There are mainly two kinds of CNN models, i.e., verification models and identification models.
Moreover, an experimental modelling and identification of the cantilever parameters are presented.
A brief summary of the models and identification methods is presented.
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