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@article{194241,
        author = {Arulmani K and S.Bharathi},
        title = {LOCAL NEUTROSOPHIC ROUGH SETS ON TOPOLOGICAL SPACE},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {4583-4589},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194241},
        abstract = {Uncertainty and incompleteness are ongoing key challenges in the fields of data analysis, decision-making, and topological modelling. To address these concerns, this paper introduces a novel framework for local neutrosophic rough sets (LNRS) within a topological space, referred to as the local neutrosophic rough topology (LNRT). Based on the rough set theory, neutrosophic sets, and their hybrid models, LNRT successfully navigates the challenges posed by indeterminacy and the significance of attributes, particularly in large-scale data analysis. Additionally, present the definitions of LNRT along with illustrative examples.},
        keywords = {Neutrosophic Set, Local Rough Set, LNRS, LNRT, LNRT- interior, LNRT- exterior, LNRT- closure.},
        month = {March},
        }