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High-fidelity data (HiFi) includes data that was produced by a person or Stochastic Process that closely matches the operational context of interest. For example, in wing design optimization, high-fidelity data uses physical models in simulation that produce results that closely match the wing in a similar real-world setting. [5]
An example of innovative simulation to study patient safety is from nursing research. Groves et al. (2016) used a high-fidelity simulation to examine nursing safety-oriented behaviors during times such as change-of-shift report. [38] However, the value of simulation interventions to translating to clinical practice are is still debatable. [40]
Even if high-fidelity computer Sims are never conscious, Dainton's reasoning leads to the following conclusion: either the fraction of human-level civilizations that reach a posthuman stage and are able and willing to run large numbers of neural ancestor simulations is close to zero, or some kind of (possibly neural) ancestor simulation exists.
Modeling and simulation (M&S) is the use of models (e.g., physical, mathematical, behavioral, or logical representation of a system, entity, phenomenon, or process) as a basis for simulations to develop data utilized for managerial or technical decision making.
A live simulation, by definition represents the highest fidelity, since it is reality. But a simulation quickly becomes more difficult when it is created from various live, virtual and constructive elements, or sets of simulations with various network protocols, where each simulation consists of a set of live, virtual and constructive elements.
Fidelity is therefore a measure of the realism of a model or simulation. [4] Simulation fidelity has also been described in the past as "degree of similarity". [5] In quantum mechanics and optics, [6] the fidelity of a field is calculated as an overlap integral of the field of interest with a reference or target field.
A validation space ("reality") represents the fine model, for example, a high-fidelity physics model. The optimization space, where conventional optimization is carried out, incorporates the coarse model (or surrogate model), for example, the low-fidelity physics or "knowledge" model. In a space-mapping design optimization phase, there is a ...
Scientific modelling is an activity that produces models representing empirical objects, phenomena, and physical processes, to make a particular part or feature of the world easier to understand, define, quantify, visualize, or simulate.