AI-Facilitated Dynamic Threshold-Tuning for a Maritime Domain Awareness Module

This paper presents a Decision Support Engine (DSE), which utilizes a unique Lower Ambiguity, Higher Uncertainty (LAHU) and Higher Ambiguity, Lower Uncertainty (HALU) Module (LHM) to facilitate decision engineering pathways under compressed decision cycles. Central to this is the identification of isomorphic paradigms, via the discernment of relevant sparse and “Very Small/Non-Obvious” (VSNO) High Dimensional Data (HDD). Accordingly, it is found that an amalgam of a particular sequence of transformations, a Robust Convex Relaxations (RCR)-centric neural network construct, and a Type II Fuzzy Set/Three-Way Soft Clustering approach (and other components buttressing the LHM) can be of value-added proposition in the challenge of employing fuzzy logic and deep learning to adaptive systems for intelligent control within this proxy as well as other domains.