Modeling, Analysis and Control of COVID-19 in Italy: Study of Scenarios

2021 ◽  
Author(s):  
Paolo Di Giamberardino ◽  
Rita Caldarella ◽  
Daniela Iacoviello
Keyword(s):  
Modeling Analysis ◽  
And Control

Modeling, Analysis, Design, and Control of Stochastic Systems

2000 ◽  
Vol 95 (451) ◽  
pp. 1018
Author(s):  
R. Dobrow ◽  
V. G. Kuklarni
Keyword(s):  
Stochastic Systems ◽  
Modeling Analysis ◽  
Analysis Design ◽  
And Control

An Optimization Procedure of Model’s Base Construction in Multimodel Representation of Complex Nonlinear Systems

2021 ◽  
Author(s):  
Bennasr Hichem ◽  
M’Sahli Faouzi
Keyword(s):  
Nonlinear Systems ◽  
Learning Algorithm ◽  
Batch Reactor ◽  
Optimization Procedure ◽  
Base Number ◽  
Deterministic Approach ◽  
Modeling Analysis ◽  
Complex Nonlinear Systems ◽  
Definition Of ◽  
And Control

The multimodel approach is a research subject developed for modeling, analysis and control of complex systems. This approach supposes the definition of a set of simple models forming a model’s library. The number of models and the contribution of their validities is the main issues to consider in the multimodel approach. In this chapter, a new theoretical technique has been developed for this purpose based on a combination of probabilistic approaches with different objective function. First, the number of model is constructed using neural network and fuzzy logic. Indeed, the number of models is determined using frequency-sensitive competitive learning algorithm (FSCL) and the operating clusters are identified using Fuzzy K- means algorithm. Second, the Models’ base number is reduced. Focusing on the use of both two type of validity calculation for each model and a stochastic SVD technique is used to evaluate their contribution and permits the reduction of the Models’ base number. The combination of FSCL algorithms, K-means and the SVD technique for the proposed concept is considered as a deterministic approach discussed in this chapter has the potential to be applied to complex nonlinear systems with dynamic rapid. The recommended approach is implemented, reviewed and compared to academic benchmark and semi-batch reactor, the results in Models’ base reduction is very important witch gives a good performance in modeling.

Modeling, analysis and control system development for the Italian hydrogen house

2009 ◽  
Vol 34 (4) ◽  
pp. 1638-1646 ◽  
Author(s):  
E.M. Stewart ◽  
A.E. Lutz ◽  
S. Schoenung ◽  
M. Chiesa ◽  
J.O. Keller ◽  
...  
Keyword(s):  
Control System ◽  
System Development ◽  
Modeling Analysis ◽  
And Control
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