Soft set theory—First results
TLDR
The main purpose of this paper is to introduce the basic notions of the theory of soft sets, to present the first results of the the theory, and to discuss some problems of the future.Abstract:
The soft set theory offers a general mathematical tool for dealing with uncertain, fuzzy, not clearly defined objects. The main purpose of this paper is to introduce the basic notions of the theory of soft sets, to present the first results of the theory, and to discuss some problems of the future.read more
Citations
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An alternative data filling approach for prediction of missing data in soft sets (ADFIS).
TL;DR: Experimental results on small, 04 UCI benchmark data and causality workbench lung cancer data shows that ADFIS performs better accuracy as compared to DFIS.
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Decision-making analysis based on bipolar fuzzy N-soft information
TL;DR: This research article presents a new framework for handling imprecisely acquired bipolar information along with parameterized graded descriptions and develops BFNS $$_\text {f}$$ -TOPSIS methods for the solution of multi- attribute decision-making (MADM) and multi-attribute group decision- making (MAGDM) problems defined by bipolar fuzzy N-soft information.
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Generalised Interval-Valued Fuzzy Soft Set
TL;DR: The concept of generalised interval-valued fuzzy soft set and its operations and some of their properties are introduced and applications of this theory in solving a decision making problem are given.
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Methods for Assessing Human–Machine Performance under Fuzzy Conditions
TL;DR: The present review summarizes the author's research on building assessment models for use in a fuzzy environment, which include the measurement of a fuzzy system’s uncertainty, the application of the center of gravity defuzzification technique, and the applications of the fuzzy relation equations.
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A state-based knowledge representation approach for information logical inconsistency detection in warning systems
Jun Ma,Guangquan Zhang,Jie Lu +2 more
TL;DR: A state-based knowledge representation approach is proposed, in which domain-specific knowledge is expressed by combinations of the relevant objects' states, which can flexibly handle the demands of various domain- specific situations through reducing part of restrictions in existing methods.
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