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Clearly, MapReduce is the most prominent model for problems of large-scale data processing.
The gradient system represents the steady-state case of reaction-diffusion system which is a model for problems arising from biology, chemistry, physics and ecology, etc.
The equilibrium problems, in its various forms, found application in optimization problems, fixed point problems, convex minimization problems; in other words, equilibrium problems are a unified model for problems arising in physics, engineering, economics, and so on (see [10]).
Although there is a variety of parallel programming models, the MapReduce paradigm is considered as the most prominent model for problems of large scale data processing of which the clustering.
The equilibrium problems, in its various forms, found application in optimization problems, fixed point problems, and convex minimization problems; in other words, equilibrium problems are a unified model for problems arising in physics, engineering, economics, and so on (see [26 29]).
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Then, the researchers use the regression method for the experimental data on controllable factors to build an empirical model for problem analysis.
They presented a bi-level model for problem in which the first level decides the design of the routes which serve the customers and the second level involved decision on the manufacturing process.
The quotient space theory proposed by Zhang is a model for problem solving with the basic idea of conceptualizing the world at different granularities and shifting the focus of thinking onto a different abstract level [54, 55].
This paper reviews recent advances in the area of surrogate models for problems in modeling, feasibility analysis, and optimization.
This feature allows a more flexible design of discrete models for problems with complicated geometries, shocks, or singular points.
In this context, machine learning algorithms, able to seek models for problems with multi-source data, have to be used.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com