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This article introduces a new model to forecast the time series data set, which is exclusively based on the neutrosophic set (NS) theory. The main objective of employing the NS theory in time series data set is that it can represent the uncertainty associated with them into three different memberships, as: truth, indeterminacy and falsity. In this study, this representation of time series data set is named as a neutrosophic time series (NTS). The proposed NTS approach is applied in forecasting the time series data set. The proposed approach has been verified and validated with benchmark data sets. Various comparative studies demonstrate the adequacy of the proposed model in forecasting the time series data set.
Keywords:
Uncertainty; Neutrosophic set; Fuzzy set; Time series forecasting.
Cite Article:
"A Neutrosophic Set Theory Based Approach for Time Series Forecasting", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 12, page no.b127-b134, December-2025, Available :http://www.ijrti.org/papers/IJRTI2512113.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator