A Neutrosophic soft topological framework for insecure intelligent decision applications

To enhance the reasoning ability when dealing with uncertainty, we hold that such a neutrosophic soft topological structure should be proposed. New classes of neutrosophic soft topology are developed by giving the mathematical structure, which involves min and max norm operations. In order to make a decision for options based on uncertain/or incomplete data, the model changes crucial topological concepts such as interior of set and closure into quantity indicators. The construction of the model was done applying topological operations to the truth degree, doubtfulness degree, and falsity degrees, and the decision criteria were formulated in form of neutrosophic soft sets. The frequency and reliability of decisions was measured by a decision index derived from these operations. Compared with fuzzy soft topological methods, experimental simulations further confirmed the effectiveness and robustness of the proposed model. The results indicated the potential ability of neutrosophic topology to be a universal mathematical tool used for intelligent devices operating in harsh and unpredictable surroundings.