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In electricity market research, the major modelling methods include optimization model based, game equilibrium model based and simulation model based.
However, limitations associated with up scaling conventional ash dispersal modelling methods include the computationally intensive nature of regional-scale applications that would require significant high-performance computing resources, long simulation times and could potentially constrain the spatial resolution, geographic extent and number of sources considered.
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Yet, our modelling methods included surveys over time within and across regions and countries, incorporated serial food balance data as covariates, and quantified resulting statistical uncertainty.
Methods include group-based trajectory modelling [10, 13] and growth mixture modelling (GMM) [11, 12].
These methods include computer modeling.
These advanced methods include computational fluid dynamics, several multiphysics modelling methods (e.g. conjugate modelling), multiscale modelling and modelling of material properties and the associated propagation of material property variability.
Other methods include food deprivation.
Such methods include zooming out.
Depending on their purpose LUCC simulation models use a sweep of different methods including suitability mapping, genetic algorithms, neural networks, scenario analysis, expert opinion, public participation or agent-based modelling [ 24].
We briefly present the modelling language in use and some features of Moby/RT, like code generation for different implementation platforms and several validation methods (including formal verification).
The modelling methods of strip plastic deformation include slab method, variation method, difference method, strip element method, and finite element method, while the modelling methods of rolls elastic deformation mainly include influence function method and finite element method.
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