Some models explain.
Today’s ecosystem models are widely compared to where climate models were in their earliest days of development, about 50 years ago.
Although neural network models enjoy tremendous advantages in handling image and text data, tree-based models still remain competitive for learning-to-rank tasks with numerical data.
Despite the obvious advantages of symbolic models there are many cases in which physical models are still useful, as in testing physical structures and mechanisms; the same is true for graphic models.
We shall discuss general models and the related Henkin models in §9.
Also very recently, Alejandro Cassini paid close attention to the nature of scientific models.
For example we obtain non-standard models of number theory, countable models of the axioms of real numbers, etc.
Peschard (2011) investigates the way in which models may be used to construct other models and generate new target systems.
Here we distinguish mechanical models from models of mechanisms and we discuss varieties of non-mechanical models.
These models include models of theory, models of experiment, and models of data (Suppes 1962, 2002).
In the genic selection case, the pluralists appear to be claiming that the genic level models are independent from the hierarchical models.
Some mechanists reserve the term “mechanical models” for models that describe the entities, activities, and organizational features of a system.
Even officers serving as generals or ministers, they all have models; even the hundred artisans performing their tasks, they too all have models.
Analogues of the above results have been proven using different game models (e.g., epistemic models, epistemic-plausibility models, etc.).
Models of ether, phlogiston, four-sex populations, and so on, are all deemed scientific models, but ether, phlogiston, and four-sex populations don’t exist.
In the DEL study of belief change, situations involving the beliefs of multiple agents are represented using a variation of basic Kripke models called plausibility models.
According to some advocates of this view, the family of models can itself be axiomatized, with those very models (or other models) serving as axiom truth-makers.
For a given purpose, there may be bad models—models that are clearly incorrect—and there may be good models, but it is unlikely that one can speak of one and only one correct model.
At this point, rather than addressing the issue of what it means for a model to represent, we focus on a number of different kinds of representation that play important roles in the practice of model-based science, namely scale models, analogical models, idealized models, toy models, minimal models, phenomenological models, exploratory models, and models of data.
The centrality of models such as inflationary models in cosmology, general-circulation models of the global climate, the double-helix model of DNA, evolutionary models in biology, agent-based models in the social sciences, and general-equilibrium models of markets in their respective domains is a case in point (the Other Internet Resources section at the end of this entry contains links to online resources that discuss these models).
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The centrality of models such as inflationary models in cosmology general-circulation models of the global climate the double-helix model of DNA evolutionary models in biology agent-based models in the social sciences and general-equilibrium models of markets in their respective domains is a case in point the Other Internet Resources section at the end of this entry contains links to online resources that discuss these models