Neutrosophic Statistical Modeling of Ecological Evaluation in Mountain Campuses: Application of Neutrosophic Moments and Bayesian Neutrosophic Inference

Abstract

Environmental monitoring in mountain campuses is often challenged by 
uncertain, incomplete, or inconsistent data. Traditional statistical models are not 
equipped to handle these ambiguities effectively. In this paper, we present a neutrosophic 
statistical framework for evaluating ecological risk in mountain environments. The model 
uses Neutrosophic Moments to compute statistical characteristics (mean, variance, 
skewness) while incorporating uncertainty and inconsistency in the data. In addition, 
Bayesian Neutrosophic Inference is applied to update ecological beliefs as new sensor 
data arrives. A custom Neutrosophic Ecological Distribution (NED) is also proposed, 
tailored for mountainous settings. The approach is fully illustrated with equations, 
numerical examples, and a real-world case study. The results show improved flexibility 
and accuracy in environmental risk assessment, especially in situations with vague or 
conflicting data. 

DOI: 10.5281/zenodo.15843819