Deep neuro-fuzzy systems (DNFSs) have been successfully applied to real-world problems
using the efficient learning process of deep neural networks (DNNs) and reasoning aptitude …

The health and productivity of animals, as well as farmers' financial well-being, can be
significantly impacted by cattle illnesses. Accurate and timely diagnosis is therefore …

For heterogeneous data sets containing numerical and symbolic feature values, feature
selection based on fuzzy neighborhood multigranulation rough sets (FNMRS) is a very …

The continuous development of industry big data technology requires better computing
methods to discover the data value. Information forecast, as an important part of data mining …

Prosumer microgrids (PMGs) are considered as active users in smart grids. These units are
able to generate and sell electricity to aggregators or neighbor consumers in the prosumer …

The single-valued neutrosophic set (SVNS) is a well-known model for handling uncertain
and indeterminate information. Information measures such as distance measures, similarity …

Context and Background: Complex fuzzy theory has a strong practical implication in many
real-world applications. Complex Fuzzy Inference System (CFIS) is a powerful technique to …

The COVID-19 pandemic continues to wreak havoc on the world's population's health and
well-being. Successful screening of infected patients is a critical step in the fight against it …

Many effective tools in fuzzy soft set theory have been proposed to handle various
complicated problems in different fields of our real life, especially in decision making …

Nowadays, there is a fresh push towards putting more attention on sustainability issues
without affecting productivity as main target in industrial cyberphysical systems. In this …