5 results about "Stochastic distribution" patented technology

The general aspects of the present disclosure relate to a method for determining a surrogate model of a state space model. The method includes receiving a time-continuous state space model describing a system to be closed-loop controlled. The method further includes forming a time-discrete representation of the state space model describing the system to be closed-loop controlled, wherein at least the time-discrete representation of the state space model has a time dependence based on a stochastic distribution. The method further includes determining a surrogate model of the time-discrete representation of the state space model.

This invention provides a method for calculating carbon emissions in a distributed generation (DG) stochastic output distribution network. The method includes: acquiring raw data of the DG stochastic output distribution network; inputting the raw data into a preset node admittance matrix to determine the distribution probability of parameters at each node in the distribution network, and performing deterministic power flow calculation based on the determined distribution probability to obtain the randomly distributed generator carbon emission intensity; calculating the corresponding judgment coefficient based on the obtained randomly distributed generator carbon emission intensity; determining whether convergence is required based on the judgment coefficient; if convergence is required, redetermining the distribution probability of each node parameter and re-performing the deterministic power flow calculation until convergence is no longer required; if convergence is not required, outputting the obtained randomly distributed generator carbon emission intensity and power flow results as the final calculation result. This invention lays a solid foundation for the comprehensive analysis and evaluation of carbon emissions under various operating conditions and meets the requirements for carbon flow calculation in distribution networks containing DG.

This invention relates to a method and system for simulating the spatial variability of concrete based on stochastic discrete element method (DEM). The method includes: modeling the concrete material using the DEM based on the Monte Carlo approach, assigning a corresponding particle contact model according to the material's mechanical characteristics; using a random seed number to characterize the random distribution of aggregates; simulating the spatial distribution characteristics of strength parameters between particles using Monte Carlo simulation based on the random aggregates; and introducing a random field into the spatial variation of strength parameters, changing the internal strength spatial distribution of the material through different random parameters. Compared with existing technologies, the numerical simulation method of this invention, based on the DEM and employing a coupling of direct and indirect methods, fully considers the random distribution of aggregates and the spatial variation of strength parameters in concrete materials, and can better reproduce the mechanical variability characteristics of concrete materials.

The invention relates to a ship berthing method and device, electronic equipment and a computer storage medium, and belongs to the technical field of maritime affairs, and the ship berthing method comprises the steps: obtaining multi-physics field data of a ship berthing area, constructing an instantaneous random distribution model of each physics field data, and determining the uncertainty of the multi-physics field data; adopting a coupling six-degree-of-freedom frequency-time domain hybrid solver to solve the joint probability response of the motion state of the ship body when the uncertainty is synchronously propagated in the ship body kinetic equation, the mooring elastic-plastic equation and the propeller kinetic equation; determining the berthing failure probability that the posture of the ship body exceeds a preset posture safety threshold value and the tension of the cable exceeds a preset tension safety threshold value, performing joint constraint optimization on the berthing failure probability and a preset berthing constraint condition, and determining a dynamic safety probability boundary of ship berthing within a preset time period; and determining a berthing scheme of the ship in a preset time period based on the dynamic safety probability boundary. The ship berthing scheme can be efficiently and automatically proposed.

The invention discloses a noise enhancement nonlinear system joint detection and estimation method under a Neyman-Pearson framework, and belongs to the field of signal processing. Firstly, independent additive noise is added to a nonlinear system input signal, and noise-corrected nonlinear system output is obtained after the nonlinear system input signal passes through the nonlinear system. And secondly, under the Neyman-Pearson criterion, performing binary hypothesis judgment based on the output, and estimating unknown parameters in the signal of which the judgment result is hypothesis H1. And under the condition of ensuring that the detection probability and the false alarm probability meet certain constraints, constructing a noise enhancement nonlinear system joint detection and estimation model which minimizes the conditional estimation risk. The additive noise is the optimal solution of the model and is random distribution formed by convex combination of not more than three constant vectors with a certain weight. According to the method, noise enhancement and nonlinear system joint detection and estimation under the Neyman-Pearson criterion are combined, and the estimation performance is further improved under the condition that the detection performance is not reduced.