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The overall purpose of DMIP 2 was to test many distributed models with operational quality data with a view towards meeting NWS operational forecasting needs.
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This paper gives the general frame of the proposed analysis model with operational steps through a case study.
This paper presents a novel development of a database model with operational procedures by using deoxyribonucleic acid (DNA) computing solution to exploit vast parallelism.
There were greater variations among the three models when critiquing model fit with operational application.
The model is provided with operational restrictions for the monotonicity of the objective function (=either only growth, or only decrease in every variable) and its quasi-concavity (=convexity of the associated preference).
Only few articles treated them as a single asset and the consequences predicted by these models showed close similarities with operational data from recently commissioned pipelines.
The model predictions are compared with operational and configuration data from two real engines and show reasonably good accuracy.
The model predictions are compared with operational data from a real power plant during a warm start-up and show reasonably good accuracy.
Furthermore, models are not typically integrated with operational information from buildings to facilitate and maintain building performance in the operational stage.
The calculations are based on 3D models with realistic geometric and operational parameters.
To investigate this, we also compare the standard symplectic Euler method, which is used in many operational models, with two improved timestepping algorithms based on SDE splitting methods.
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