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Rough set feature selection approach has proven to be an efficient mathematical tool based on upper and lower approximation.
The aim of this work was to design an mathematical tool based on documented data, that would predict the risk of metastatic involvement for each nodal station.
The aim of this study was to design a mathematical tool based on documented data to predict the risk of metastatic involvement for each nodal station.
The work presented is focused on the development of an innovative mathematical tool based on the particle-in-cell method (PIC) for the simulation of the soot distribution inside a single channel of a diesel particulate filter.
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Energy models are valuable mathematical tools based on the systems approach.
In this work, we present a decision-support tool based on mathematical programming for the design of solar assisted absorption cooling systems.
This paper presents a decision support tool based on mathematical diffusion that evaluates the adoption levels of different schemes or pathways towards reducing GHG emissions in housing stock.
The mathematical tools are based on the kernel estimators technique.
The last two decades have seen tremendous activity in the development of new mathematical and computational tools based on multiscale ideas (wavelet).
The mathematical tool is constructed based on a new infinite dimensional vector space utilizing multiplication of exponential functions as a base for Fourier series in the tangential direction and Bessel function as a base in the radial direction.
Within the context of decision-support tools based on mathematical programming techniques, this contribution presents a procedure for constraints identification and classification.
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