Neutrosophic Soft Rough Graphs With Application
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Neutrosophic Soft Rough Graphs with Application
Neutrosophic sets (NSs) handle uncertain information while fuzzy sets (FSs) and intuitionistic fuzzy sets (IFs) fail to handle indeterminate information. Soft set theory, neutrosophic set theory, and rough set theory are different mathematical models for handling uncertainties and they are mutually related.
Soft Rough Neutrosophic Influence Graphs with Application
In this paper, we apply the notion of soft rough neutrosophic sets to graph theory. We develop certain new concepts, including soft rough neutrosophic graphs, soft rough neutrosophic influence graphs, soft rough neutrosophic influence cycles and soft rough neutrosophic influence trees. We illustrate these concepts with examples, and investigate some of their properties. We solve the decision-making problem by using our proposed algorithm.
Neutrosophic Soft Rough Topology and its Applications to Multi-Criteria Decision-Making
In this manuscript, we introduce the notion of neutrosophic soft rough topology (NSR-topology) defined on neutrosophic soft rough set (NSR-set). We define certain properties of NSR- topology including NSR-interior, NSR-closure, NSR-exterior, NSR-neighborhood, NSR-limit point, and NSR-bases. Furthermore, we aim to develop some multi-criteria decision-making (MCDM) methods based on NSR-set and NSR-topology to deal with ambiguities in the real-world problems. For this purpose, we establish algorithm 1 for suitable brand selection and algorithm 2 to determinencore issues to control crime rate based on NSR-lower approximations, NSR-upper approximations, matrices, core, and NSR-topology.