Starting from real data, when modeling we build a theoretical structure
The action of modeling refers to the construction of a scheme or a model . A model, meanwhile, is a small-scale representation of something or an archetype that serves as a reference .
Development of a theoretical model
Many times modeling is used as a synonym for modeling . However, there are differences between both concepts. According to the Royal Spanish Academy ( RAE ), modeling can refer to configuring something or sticking to a model .
Returning to the idea of modeling, it is usually used specifically with respect to the development of a theoretical model . Thus, whoever is in charge of modeling something uses theory to predict or infer a situation derived from the established assumption. The process can also contribute to the presentation of a simplified version of a reality.
It is important to note that technical or scientific knowledge is not necessary to model something. Although thanks to them it is possible to carry out research that can solve some of the most serious problems of humanity, we all have the ability to translate a situation or phenomenon into theory and we make use of it even if we do not know it, every once we get ahead of the facts based on our experience.
Example of «model»
Take the case of global warming . Many scientists affirm that the average temperature of planet Earth has been increasing as a consequence of human activity, especially due to the emission of greenhouse gases. This warming generates multiple problems, such as melting glaciers and rising sea levels. To show the possible effects of a specific increase in temperature, experts tend to model warming : for example, showing what would happen if an average rise of 0.5 degrees Celsius were recorded at the planetary level.
This example serves to show that the action of modeling is usually used in cases of certain risk, whose consequences may be negative for the world. We do not model a situation such as our piano lessons to see how much we could improve, because unless we stop trying there is no chance of failure. On the other hand, the advance of pollution will undoubtedly affect us negatively, sooner or later, with greater or lesser severity.
Methods
It is common to use algorithms and artificial intelligence to model. In this way, based on data, it is possible to analyze the impact of the climate or the economy on a community, to mention two possibilities.
We understand by algorithm any set of operations that are systematically repeated and that give us the opportunity to calculate and solve a specific kind of problem. In other words, it is a kind of "recipe" that has a very specific purpose. An example is the one used to know the square root of a given number: although the latter may always be different, the steps for the calculation are always the same.
Modeling also serves to anticipate the impact of global warming
Regarding its use for modeling, it is first necessary to know the characteristics of the area in which it is to be applied, to develop an appropriate algorithm . Climate and the economy are two very different topics, so they require different methods as well. Each field is tied to certain variables, constants and special cases that must be taken into account to create the correct functions .
Then we have artificial intelligence , which considerably accelerates research processes, because it makes estimates at a speed impossible to achieve by the human brain and offers potential solutions to problems of all kinds. In contrast to an algorithm that does not vary, artificial intelligence learns with each use, so that it evolves beyond its initial state.