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It is a stochastic parameter.
We depict generator's decision making as two stochastic parameter linear programming models.
By augmenting system states, measurements and new defined variables, the original system is transformed into the stochastic parameter one.
Stochastic parameter sets are sometimes used to account for the effects of spatial variability at the field scale.
In this model, a scenario is a sequence of tree nodes and a scenario is a deterministic parameter equivalent to stochastic parameter.
Our main objective is to obtain local stability of mild solutions for stochastic parameter systems, with two novelties when compared with the former work in this area: 1.
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Based on the above two points, a stochastic parameter-varying Markovian jump system (SPVMJS) is constructed.
Demands have been considered as stochastic parameters.
Stochastic parameters a = 1 km and ε = 0.03 are assumed.
These stochastic parameters are characterized by a scenario tree.
Stochastic parameters a = 1 km and ε = 0.03 and wavenumber k=π km−1 are assumed.
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