aspg-24-4493-1791482607 20261008180327 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Neutrosophic and Fuzzy Systems JNFS 2771-6430 2771-6449 2025 10 2 Ahmed Hatip Department of Mathematics, Gaziantep University, Gaziantep, Turkey Three reconstructions of the same missing cell can each be defensible and still disagree materially. Let e=(eN,eS,eR) denote contextual-neighborhood, low-rank, and cross-variable ridge estimates. The central question is therefore not only which value should replace xi j, but how much coherent evidence supports that replacement. Neutrosophic–Fuzzy Multi-View Imputation (NFMVI) addresses this question by assigning each source a fuzzy reliability μs ∈ (0,1] and a Gaussian concordance as = exp[−(es−c)2/(2γ2)] around a reliability-weighted center c. These quantities generate the source state (Ts, Is,Fs) = (μsas,1−as,1− μs), from which ws = Ts/Σr Tr yields the convex reconstruction bx = Σswses. The same state produces a cell-level unresolved-evidence fraction U = 1−Σs Ts/Σs(Ts+Is+Fs), so reconstruction and uncertainty are generated by one mechanism rather than by separate post-processing. Evaluation uses two real multivariate datasets, MCAR, value-dependent MAR, and structured channel deletion at 10–30%, giving 144 common deterministic masks. The evidence is deliberately mixed. On the macroeconomic panel, NFMVI attains standardized RMSE 0.3425, below KNN (0.3776), Bayesian-ridge chained imputation (0.3794), and iterative SVD (0.4987); on the diabetes covariates, NFMVI (0.7641) and chained imputation (0.7659) are nearly indistinguishable overall, with chained imputation remaining better under MAR. The uncertainty signal is more distinctive: macro error-screening AUC averages 0.8156, and RMSE rises from 0.1717 in the lowest-U quartile to 0.6202 in the highest. Paired bootstrap contrasts, correlation-structure error, ablation, and parameter sensitivity therefore support a narrower conclusion than universal accuracy dominance: NFMVI provides an interpretable fuzzy–neutrosophic rule for reconciling heterogeneous imputers while retaining cell-level evidence conflict for downstream scrutiny. 2025 01 09 4493 https://creativecommons.org/licenses/by/4.0/ 10.54216/JNFS.100201 https://www.americaspg.com/journal/24/article/4493 https://www.americaspg.com/storage/articles/manuscripts/01M0GXTYR4Y920P32ACAJBTJDR.pdf