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The developed theoretical methods and stochastic inequalities techniques can be applied to explore the high-dimensional nonlinear stochastic differential systems.
The developed theoretical methods and stochastic inequalities technique can be used to investigate the high-dimensional nonlinear stochastic differential systems.
Derivative-based optimization methods and stochastic optimization methods are quite different techniques, with different drawbacks and potentialities.
Methods include the stochastic Galerkin methods based on generalized Polynomial Chaos (gPC), stochastic collocation methods and stochastic finite volume methods (SFVM).
Optimizing problems can be warranted by different methods which can be split into two major groups; deterministic methods and stochastic methods.
Machine learning approaches, such as those using reinforcement learning methods and stochastic models, have been used to acquire behavior appropriate to environments characterized by uncertainty.
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As optimization techniques, direct search method and stochastic search method are widely used in designing of ship structures.
Then, a fine single sand body reservoir geological model was constructed using a combination of a determined modelling method and stochastic modelling method.
By using the Lyapunov method and stochastic analysis, we derive a sufficient condition for the existence of the desired estimator.
Based on the stochastic Kronecker delta function method and stochastic analysis technique, we establish some conditions for the sake of guaranteeing the existence of the desired state estimator.
Three semi-analytical methods, namely the Describing Function Method, Multi-term Harmonic Balance Method and Stochastic Linearization Method, are utilized to investigate the effect of impact damping.
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