loading...| Preferred Name |
model |
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| Synonyms |
computational models computer-simulation model Simulation model computer-simulation models mathematical model mathematical models computational model simulation model simulation models analytical classical model models |
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| Definitions |
A mathematical model is the use of mathematical language to describe the behaviour of a system. A mathematical model usually describes a system by a set of variables and a set of equations that establish relationships between the variables. The variables represent some properties of the system, for example, measured system outputs often in the form of signals, timing data, counters, event occurrence (yes/no). The actual model is the set of functions that describe the relations between the different variables. [source: WordIQ online dictionary] |
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| ID |
http://purl.org/obo/owl/SBO#SBO_0000004 |
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| comment |
Types Computer models can be classified according to several independent pairs of attributes, including: * Stochastic or deterministic (and as a special case of deterministic, chaotic) - see External links below for examples of stochastic vs. deterministic simulations * Steady-state or dynamic * Continuous or discrete (and as an important special case of discrete, discrete event or DE models) * Local or distributed. Equations define the relationships between elements of the modeled system and attempt to find a state in which the system is in equilibrium. Such models are often used in simulating physical systems, as a simpler modeling case before dynamic simulation is attempted. * Dynamic simulations model changes in a system in response to (usually changing) input signals. * Stochastic models use random number generators to model chance or random events; * A discrete event simulation (DES) manages events in time. Most computer, logic-test and fault-tree simulations are of this type. In this type of simulation, the simulator maintains a queue of events sorted by the simulated time they should occur. The simulator reads the queue and triggers new events as each event is processed. It is not important to execute the simulation in real time. It's often more important to be able to access the data produced by the simulation, to discover logic defects in the design, or the sequence of events. * A continuous dynamic simulation performs numerical solution of differential-algebraic equations or differential equations (either partial or ordinary). Periodically, the simulation program solves all the equations, and uses the numbers to change the state and output of the simulation. Applications include flight simulators, construction and management simulation games, chemical process modeling, and simulations of electrical circuits. Originally, these kinds of simulations were actually implemented on analog computers, where the differential equations could be represented directly by various electrical components such as op-amps. By the late 1980s, however, most "analog" simulations were run on conventional digital computers that emulate the behavior of an analog computer. * A special type of discrete simulation which does not rely on a model with an underlying equation, but can nonetheless be represented formally, is agent-based simulation. In agent-based simulation, the individual entities (such as molecules, cells, trees or consumers) in the model are represented directly (rather than by their density or concentration) and possess an internal state and set of behaviors or rules which determine how the agent's state is updated from one time-step to the next. * Distributed models run on a network of interconnected computers, possibly through the Internet. Simulations dispersed across multiple host computers like this are often referred to as "distributed simulations". There are several standards for distributed simulation, including Aggregate Level Simulation Protocol (ALSP), Distributed Interactive Simulation (DIS), the High Level Architecture (simulation) (HLA) and the Test and Training Enabling Architecture (TENA). source: http://en.wikipedia.org/wiki/Computer_model#Types |
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| definition |
A mathematical model is the use of mathematical language to describe the behaviour of a system. A mathematical model usually describes a system by a set of variables and a set of equations that establish relationships between the variables. The variables represent some properties of the system, for example, measured system outputs often in the form of signals, timing data, counters, event occurrence (yes/no). The actual model is the set of functions that describe the relations between the different variables. [source: WordIQ online dictionary] |
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| exact_synonym |
computational models computer-simulation model Simulation model computer-simulation models mathematical model mathematical models computational model simulation model simulation models analytical classical model models |
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| label |
model |
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| PMID |
19768802 |
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| prefixIRI |
sbo:SBO_0000004 |
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| prefLabel |
model |
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| related_synonym |
solvent primitive model voxelized models realistic physiological multiscale model discretized models animal model animal models CG AuNPs model model system field model Pattern-Oriented Modelling individual-based model current theoretical models many-state model multiprobe freezing model Point-light actors atomic model atomic models 3D reconstruction model Pattern-Oriented Model Pattern-Oriented Models multiscale modeling theoretic models FitzHugh-Nagumo bead models Mathematical modelling predictive model protein model Compound Symmetry covariance model anatomic simulators perception-like situation models topology-based coarse-grained modeling agent-based spatially explicit simulation model mathematical modeling hybrid programming models restricted primitive model model complex staggered timing model DK-QN model lake specific models coarse-grained model coarse-grained models trabecular bone remodeling multiscale model multiscale models in vivo model simulated patients polymer model complex models coarse-grained (CG) models simulation model of Aedes aegypti populations decision-analytic computer-simulation model remodelling processes CellML models vitamin D forced model GLOPEM-CEVSA model GLOPEM-CEVSA models protein models comparative modeling traditional clinical model Modeling E.coli fate and transport primitive chain network model Carnegie Ames Stanford Approach Computational modeling live porcine model remodelling coarse-grained (CG) model ten Tusscher (TT04) models GastroPlus modeling polymer models rat migraine model ten Tusscher 3D MIKE SHE groundwater resource model AR models CASA CASA model CG model DK-model FHN Hinge PLA PLAs TT04 bead model manikin manikins modeled remodeling slab model |
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