Soft set (SS) theory was introduced by Molodtsov to handle uncertainty. It uses a family of subsets associated with each parameter. Hybrid models have been found to be more useful …
K Saraf, K Bajar, A Jain, A Barve - Journal of Modelling in …, 2024 - emerald.com
Purpose This study aims to determine the barriers hindering the incorporation of blockchain technology (BCT) in two key service industries–hotel and health care–as well as to assess …
There are several models of uncertainty found in the literature like fuzzy set, rough set, soft set and hesitant fuzzy set. Also, several hybrid models have come up as a combination of …
Soft set is one of the latest mathematical models to handle uncertainty. In a soft set, every element of its parameter set is associated with a subset of the universe of discourse under …
TR Sooraj, BK Tripathy - International Journal of Fuzzy System …, 2018 - igi-global.com
As seed selection is a challenging task due to the presence of hundreds of varieties of seeds of each kind, some homework is necessary for selecting suitable seeds as new varieties and …
Decision making has become a common feature in day-to-day activities. Uncertainty-based models are more efficient in handling such problems. In this chapter, we propose an …
TR Sooraj, BK Tripathy - Artificial Intelligence and Evolutionary …, 2017 - Springer
Molodtsov introduced soft set theory in 1999 to handle uncertainty. It has been found that hybrid models are more useful than that of individual components. Yang et al. introduced the …
RK Mohanty, BK Tripathy, SC Parida - Computational Intelligence in Data …, 2022 - Springer
Covid-19 is one of the biggest pandemics in the history of mankind. It has kept the modern world hostage for more than one and a half years now. Strict lockdown is creating more …
There are several models of uncertainty found in the literature like fuzzy set (FS), rough set, intuitionistic fuzzy set, soft set, and hesitant fuzzy set. Also, several hybrid models have come …