aspg-39-4339-1792222363 20261017073243 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Neutrosophic and Information Fusion NIF 2836-7863 2025 5 1 Samandarboy Sulaymanov Tashkent state university of economics, Uzbekistan Maha Ibrahim Tashkent state university of economics, Uzbekistan Multi-source decision systems require a representation in which supportive evidence, contradictory evidence, and weak evidence are not collapsed into the same numerical channel. This paper develops a dynamic reliability-kernel model for single-valued neutrosophic evidence fusion. Given a matrix of source signals, each source is transformed into a single-valued neutrosophic triplet whose truth, indeterminacy, and falsity memberships are governed by signed evidence strength. A time-varying reliability kernel then assigns larger mass to sources with lower recent instability, and a dispersion-augmented fusion operator produces a global neutrosophic state. The final decision rule is formulated as a penalized neutrosophic score and as a regularized probabilistic classifier over the fused triplet. The model is evaluated on a public weekly stock dataset containing six technology-market sources. The results show that the proposed representation achieves competitive chronological classification performance while providing explicit mathematical control over indeterminacy, disagreement, and reliability. Ablation and penalty-sensitivity analyses demonstrate that indeterminacy is a functional component of the decision model rather than a cosmetic label. The paper offers a reproducible mathematical framework for neutrosophic information fusion in uncertain intelligent decision-support systems. 2025 10 16 4339 https://creativecommons.org/licenses/by/4.0/ 10.54216/NIF.050102 https://americaspg.com/journal/39/article/4339 https://americaspg.com/storage/articles/manuscripts/01M0V5V0N1EHVMTJDA4A004BQR.pdf