Malaysian Journal of Mathematical Sciences, September 2026, Vol. 20, No. 3
Analysis of Dengue Fever Data using Neighborhood Based Infra-Topological Approximation Spaces
Madan, P. and Tripathi, A.
Corresponding Email: alka.tripathi@mail.jiit.ac.in
Received date: 23 October 2024
Accepted date: 12 December 2025
Abstract:
With an objective to enhance the approximation space, this paper integrates an infra-topological structure with three distinct neighborhood systems: $\mathfrak{j}$, $\mathfrak{j}$-adhesion and $\mathbb{E}_{\mathfrak{j}}$ neighborhoods. The infra-topological structure is less rigorous than classical topological spaces and offers greater flexibility in modeling uncertainty and vagueness. It has applications in attribute reduction, medical diagnosis, granular computing, etc. ${\aleph}_\mathfrak{j}$, $\mathfrak{j}$-adhesion and $\mathbb{E}_\mathfrak{j}$-infra-topological spaces are introduced from the corresponding neighborhood systems under the binary relation. The relationships between infra-topologies are investigated under the binary relation. These infra-topologies are subsequently utilized to define the infra-${\aleph}_\mathfrak{j}$, infra-$\mathfrak{j}$-adhesion and infra-$\mathbb{E}_\mathfrak{j}$ approximation operators. The key benefit of these models is that they maintain the properties of Pawlak approximation operators. A distinctive feature of the current approach is that all accuracy measures remain identical (one) when applied under a reflexive relation. The dengue fever information system is analyzed by proposed methods, which effectively reduce the diagnostic vagueness and improve decision-making. The strengths and limitations of the current approaches are mentioned in the paper.
Keywords: rough set; $\mathfrak{j}$-neighborhoods; dengue fever; infra-topology; accuracy measure.
