Based on mathematical uses of formulas in science. How can i discriminate between simulation and modeling terms ? Especially in writing papers. Please, advise.
Modeling is the process of producing a model; a model is a representation of the construction and working ofsome system of interest. A model is similar to but simpler than the system it represents. One purpose of a model is to enable the analyst to predict the effect of changes to the system. On the one hand, a model should be a close approximation to the real system and incorporate most of its salient features...
A simulation of a system is the operation of a model of the system. The model can be reconfigured and experimented with; usually, this is impossible, too expensive or impractical to do in the system it represents. The operation of the model can be studied, and hence, properties concerning the behavior of the actual system
or its subsystem can be inferred. In its broadest sense, simulation is a tool to evaluate the performance of a system, existing or proposed, under different configurations of interest and over long periods of real time.
Simulation is used before an existing system is altered or a new system built, to reduce the chances of failure to meet specifications, to eliminate unforeseen bottlenecks, to prevent under or over-utilization of resources, and to optimize system performance...
Modeling is the process of producing a model; a model is a representation of the construction and working ofsome system of interest. A model is similar to but simpler than the system it represents. One purpose of a model is to enable the analyst to predict the effect of changes to the system. On the one hand, a model should be a close approximation to the real system and incorporate most of its salient features...
A simulation of a system is the operation of a model of the system. The model can be reconfigured and experimented with; usually, this is impossible, too expensive or impractical to do in the system it represents. The operation of the model can be studied, and hence, properties concerning the behavior of the actual system
or its subsystem can be inferred. In its broadest sense, simulation is a tool to evaluate the performance of a system, existing or proposed, under different configurations of interest and over long periods of real time.
Simulation is used before an existing system is altered or a new system built, to reduce the chances of failure to meet specifications, to eliminate unforeseen bottlenecks, to prevent under or over-utilization of resources, and to optimize system performance...
representation of any physical system in the mathematical equations format such as differential equations linear or nonlinear etc.. is called modeling, and simulation means implement these equation in computer software to get the dynamic characteristic as real system behaves.
Hello Karobi Borah,
Modelling is used for representing and clarifying theoretical concepts whose understanding is difficult. On such occasions, scholars develop models which are a miniature replica of the real phenomenon. In point of fact, through scientific modeling , scientists try to delineate and predict the behavior of conceptually complex theoretical issues pictorially - in more straightforward and tangible ways . By contrast, simulation is another scientific method which provides an operational display of how a complex theory works in real life. Therefore, it can be stated that modeling and simulation are two sides of the same coin , but they should be regarded as contrived approximations to real-world experimentations.
Best regards,
R. Biria
I think, Dr. Reza Diria is right. It is difficult to say some better.
Some in addition. In the infinitesimal (continual and hyper-continual) cases, modeling is explicitly or implicitly based on the Löwenheim–Skolem theorem and, thereby, the axiom of choice. In contrary, simulation in the proper sense of the word should be carried out on sets of the same power as the simulated object/process itself. If power is reduced during the simulation, the last is may be interpreted as modeling.
In the discrete (finite or countable) system modeling, all said above remain true, but the Löwenheim–Skolem theorem is used in the reversed direction.
A model is a schematic representation of nature or a phenomenon. More generally, a model explains how it is done and how the universe it works from a quantitative and qualitative point of view. The difference between a model and the phenomenon it wants to represent and explain is the same difference between the identikit of a person or even the photograph of a person and the person itself in flesh and bone. Any model is based on a number of variables and a number of parameters interconnected by one or more mathematical equations. For example, Von Bertalanffy's growth model is based on two variables: the expected or average length at time (or age t) lt and time (or age) t; three parameters: the asymptotic average length L∞ (i.e. the maximum theoretical length reachable by the species); the so-called Brody growth rate coefficient k (i.e. a parameter that takes into account the growth rate k); a parameter that represent the time or age when the average length was zero t0 (i.e. a parameter that takes into account the length at birth). The equation that interconnects variables and parameters is: lt = L∞ {1 - exp [-k (t-t0)]}. Is it possible to describe and measure the very complex phenomenon of the growth of a living being with two variables, three parameters, and this simple equation? Surely not, because growth depends on a large number of variables and a large number of parameters. However, this simple mathematical model is very useful and very used in the stocks assessment of fishable resources. Additionally, "playing" with the three above mentioned parameters you can simulate different growth scenarios and assess the consequences and similarities with current events. In conclusion a mathematical model allows to represent a certain phenomenon and to simulate and evaluate different scenarios and their stochastic evolution.
Excellent responses.
If you just look at the real-world, an airplane for example, you can do it without any “modeling.” I would say that modeling is the tool which allows you to deal with and affect the real world. In the plane case, this means that you want to be the one to make the plane fly and then, maybe to fly better. This requires a “mathematical model” of the real thing, a model that youy can use for design.
If first models were simply algebraic, such as F=ma, pretty soon people discovered that differential equations give pretty good and useful representations of the real-world thing, usually named the Plant. Now, you would want the Model to be a faithful representation of the Plant, no matter how large and how complex the Plant is. However, your model cannot be better than the best knowledge you have of the Plant. So, on one hand you find out that the knowledge is not complete when you start modeling and actually, modeling may help you understand the real Plant. Besides, even if you know the plant and can build a Model of the same order as the plant, even if this order is 20, 500 or 2000, soon you find out that Math cannot deal with differential equations of large order. Therefore, you try to build mathematical models that approximate the most important features of the real plant. Also, a simple model may help you understand the behavior of the plant. So, you use a reduce-order model to design what you assume can operate the Plant.
However, you do not directly take the design result that was based on a reduced-order model and immediately put it on a plane and let it fly.
So, first you test the behavior in simulation. Still, simulation cannot use the real plant, so it means running the model on a computer and see how it behaves. The first simulations may use the same reduced order model that was used for design, just to test that the design had no flaws. Then, if you know better, you can afford to complicate the model and use the most complex model in simulation, so as to raise the chance of your design to behave well with the real Plant.
It is a good question. Félicitations.
It can be compared with the différence of formula and diagramme for flowers, etc.
But only in theoretical science.
Sure, in application we need to know strict and correct determination.
Modeling refers to forming mathematical equations, replicating the behavior or response of a real world system or process to different inputs scenarios.
We cannot conduct an experiment on a real world large scale systems to observe the response of it for different inputs & disturbances. This can be done on a Model modeled.
Simulation, the way of testing the behavior of the model with various scenarios using a digital computer.
So, Simulation is done once after completing modeling !!!
Modeling mean make a abstraction of real system: make description of system that you want to analyze. You can use a mathematical or graphical.....modeling. That step allow define a static description of real system. But, if you want analyze her behavior (integrate the time) you must simulate it by using specific software for simulation and analyse performance of system.
The modeling-simulation is an approach that you allow to analyze and increase the performance of real system.
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