Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
A review on soft set-based parameter reduction and decision making
Many real world decision making problems often involve uncertainty data, which mainly
originating from incomplete data and imprecise decision. The soft set theory as a …
originating from incomplete data and imprecise decision. The soft set theory as a …
Multi-criteria decision-making model based on picture hesitant fuzzy soft set approach: An application of sustainable solar energy management
This study addresses the optimization of energy management within corporations to reduce
expenditures and maximize profits. Focusing on proactive, coordinated, and systematic …
expenditures and maximize profits. Focusing on proactive, coordinated, and systematic …
A new approach to interval-valued fuzzy soft sets and its application in decision-making
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 …
subsets associated with each parameter. Hybrid models have been found to be more useful …
Fuzzy soft set theory and its application in group decision making
Soft set 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 than the …
associated with each parameter. Hybrid models have been found to be more useful than the …
A new approach to neutrosophic soft sets and their application in decision making
In literature, several models which can handle uncertainty in datasets have been introduced.
Fuzzy set introduced by Zadeh in 1965, is one of the earliest such models and Atanassov …
Fuzzy set introduced by Zadeh in 1965, is one of the earliest such models and Atanassov …
On intuitionistic fuzzy soft set and its application in group decision making
Soft set theory introduced by Molodtsov is a new mathematical approach to handle the
uncertainty problems. It is a family of subsets associated with each parameter in a soft …
uncertainty problems. It is a family of subsets associated with each parameter in a soft …
Hesitant fuzzy soft set theory and its application in decision making
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 …
set and hesitant fuzzy set. Also, several hybrid models have come up as a combination of …
Interval valued hesitant fuzzy soft sets and its application in stock market analysis
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 …
hybrid models are more useful than that of individual components. Yang et al. introduced the …
An interval valued fuzzy soft set based optimization algorithm for high yielding seed selection
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 …
of each kind, some homework is necessary for selecting suitable seeds as new varieties and …
Improved decision making through IFSS
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 …
models are more efficient in handling such problems. In this chapter, we propose an …