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Found 3 papers, 0 papers with code
An Improved Mathematical Model of Sepsis: Modeling, Bifurcation Analysis, and Optimal Control Study for Complex Nonlinear Infectious Disease System
The difference between the RNN-BO algorithm from other optimization algorithms is that once given any new initial system value setting (initial value is associated with the initial conditions of patients), the RNN-BO algorithm is capable of quickly predicting a corresponding time-series optimal control based on the historical optimal control data for any new sepsis patient.
High-dimensional Bayesian Optimization Algorithm with Recurrent Neural Network for Disease Control Models in Time Series
Bayesian Optimization algorithm has become a promising approach for nonlinear global optimization problems and many machine learning applications.
High dimensional Bayesian Optimization Algorithm for Complex System in Time Series
Our computational experiments demonstrated that the proposed Bayesian optimization algorithm could achieve reasonable solutions with excellent performances for high dimensional global optimization problems with a time-series optimal control model.
