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Published in 2019 at "Neural Computing and Applications"
DOI: 10.1007/s00521-019-04423-2
Abstract: Existing classification techniques that are proposed previously for eliminating data inconsistency could not achieve an efficient parameter reduction in soft set theory, which effects on the obtained decisions. Meanwhile, the computational cost made during combination…
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Keywords:
reduction;
binary particle;
algorithm;
parameter reduction ... See more keywords
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Published in 2021 at "Physical review. E"
DOI: 10.1103/physreve.104.024407
Abstract: Boltzmann machines (BMs) are widely used as generative models. For example, pairwise Potts models (PMs), which are instances of the BM class, provide accurate statistical models of families of evolutionarily related protein sequences. Their parameters…
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Keywords:
parameter reduction;
parameter;
boltzmann machines;
protein ... See more keywords
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Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2940484
Abstract: The fuzzy soft set (FSS) that combines soft set theory with fuzzy set theory has been introduced to deal with uncertainty in many practical decision-making problems. However, there exist some less important and superfluous information…
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Keywords:
fuzzy soft;
parameter reduction;
reduction;
decision ... See more keywords
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Published in 2022 at "Symmetry"
DOI: 10.3390/sym14081719
Abstract: A fuzzy soft set is a mathematical tool used to deal with vagueness and uncertainty. Parameter reduction is an important issue when applying a fuzzy soft set to handle decision making. However, existing methods neglect…
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Keywords:
approach;
soft sets;
parameter reduction;
fuzzy soft ... See more keywords