Neutrosophic Cubic Correlation Fusion with Jensen–Shannon
Divergence Weighting for Multi-Pollutant Urban Air Quality
Index Estimation
Anvar Suleymanov1,*, Murod Khidoyatov2
1Central Asian University
2Tashkent state university of economics, Tashkent, Uzbekistan
Emails: a.suleymanov@centralasian.uz; mxidoyatov@gmail.com
Abstract
Estimating whether ambient air quality exceeds regulatory thresholds requires combining evidence from multiple co-measured
pollutants whose concentrations are simultaneously uncertain, interdependent, and subject to instrument noise. This paper
introduces a Neutrosophic Cubic Correlation Fusion (NC-CF) model that represents each pollutant observation as a neutrosophic
cubic value—a structure that simultaneously encodes an interval-valued membership [𝑇𝐿 , 𝑇𝑈] capturing measurement uncertainty
and a crisp neutrosophic triple (𝑡, 𝑖, 𝑓 ) capturing the nominal risk assessment—and then quantifies closeness to ideal pollution
profiles through a novel neutrosophic cubic correlation coefficient (NCC). Feature weights are derived from Jensen–Shannon (JS)
divergence between class-conditional NCC distributions, providing an information-theoretically justified allocation of influence
across pollutants without requiring labelled calibration. Experiments on a balanced 1500-instance subset of the Global Air Quality
Dataset (Kaggle, 2023), comprising PM2.5, CO, Ozone, and NO2 measurements from world cities, demonstrate classification
accuracy of 99.0% and AUC of 0.9996 under ten-fold cross-validation, matching or exceeding Logistic Regression, Decision
Tree, Random Forest, and Gradient Boosting Trees. A systematic sensitivity analysis over the interval-to-crisp interpolation
parameter 𝜆 ∈ [0, 1] reveals stable performance across the full range, confirming that the NCC’s interval component does not
introduce instability. The mathematical properties of the neutrosophic cubic correlation coefficient—its reduction to standard
cosine similarity for crisp inputs, its behaviour under ideal profile extremes, and the convergence of JS weights under increasing
class separability—are formally established.
Keywords: Neutrosophic cubic sets; Interval neutrosophic membership; Correlation coefficient; Information fusion;
Jensen–Shannon divergence; Air quality index; Multi-pollutant integration; Ideal profile; Sensitivity analysis