1.) Association between model and experimental frame. The converse of applicable to. A system accommodates an experimental frame just in case the experimental frame is applicable to the model
2.) Association between system and experimental frame . The converse of applicable to. A system accommodates an experimental frame just in case the experimental frame is applicable to the system
Process of gaining approval for model use. usually depends of prior verification and validation
Process of mapping a source model, called a base model into a target model, called a lumped model. This process involves grouping base model elements and combining each such group into a single lumped model element. Grouped elements thus become indistinguishable in the target model. Aggregation is a simplification procedure and a form of abstraction. usually done with the intention of creating a homomorphic model representation within an experimental frame other meanings.
(verb) collecting data elements together without loss of identity (in database literature)
Well-defined set of steps for executing a computational task.
a (simulator) of a model may be such an algorithm
Amount of Detail
The degree to which details are included in a model description. the amount of detail is a product of the scope and the resolution of the model.
Relation containing pairs of experimental frames and models where the experimental frame is applicable to the model the relation is many-to-many. Many models may accommodate the same experimental frame; likewise many experimental frames may be applicable to the same.
(Also ‘applies to’): Association between experimental frame and a model
(Informal): Answers the question whether it is possible to perform the experiments characterized by the experimental frame on the
(Formal): This association holds just in case the experimental frame is derivable from the scope frame of the model
Of model. Synon. variable of model
Model, which is not affected by any input
1.) Source model in an aggregation or other simplification procedure
2.) Conceptually complete representation of all aspects of interest in a modeling study, hence having the widest scope frame of interest
Collection of trajectories. Specific form of data observable in system or generated by a simulator over time within an experimental frame
Fitting a behavior to match corresponding portions of observed system behavior by adjusting model parameters
(Of a model): Intrinsic difficulty in simulating a model. The minimal resources (time, space, etc.) required to by any simulator for correct simulation. Typically, the complexity increases with the amount of detail, i.e., simulating a model that has many components, and interactions, each described with high resolution is likely to require great resource consumption no matter what simulator is used. Under this assumption, for fixed resource availability, there must be a tradeoff between scope and resolution in a simulated model.
Identifiable part of model. The model is composed of its components
Simulation in which human interaction with the execution is limited to observation. Contrasts with interactive simulation.
(Association between a simulator and a model). A simulator correctly simulates a model if it is guaranteed to faithfully generate the models behavior in every simulation run.
Cross model Validity
The consistency of a model behavior or structure with another model behavior or. Usually not feasible to established by direct comparison, but may be possible by proof of homomorphism
Material of information, system, behavior or model behavior are collections of time-indexed data.
Relation-containing pairs of experimental frames such that the first is derivable from the second
Association between a pair of experimental frames
(Informal): Answers the question of whether any experiment that can be performed within the first experimental frame can also be performed within the second
(Formal): See Multifaceted Modeling and Discrete Event Simulation
(Informal): Model description including its components variables and interactions.
A model in which the input and state determine the next state and output. If the model is autonomous then the current state by itself uniquely determines the next state and output
Simulator whose operation is distributed over distinct processing nodes (possibly geographically remote). The model being simulated may also be distributed among the nodes. Also related to parallel simulator and concurrent simulator
Dynamic Modeling Formalism
Modeling formalism capable of expressing models that generate trajectories assumes overtime.