Dynamic Membership Functions for Context-Based Fuzzy Systems

In fuzzy systems, membership functions determine the groups to which a variable can belong to, and these are static or only have one setting in some aspect. However, systems typically require model dynamic environment they represent. Still, this behavior does not reflect conventional way. Thus, capable of reflecting dynamics real-time context. The approach presented consists system where transformations, according contextual variables that influence them, adjusts real time. functions' dynamism is achieved because form sets be transformed; maximum degree set range zero one; and, location discourse universe vary dynamically. results show feasibility context-based with built-in time, has been influenced by variables. Therefore, unlike other proposals, allows modeling context on system, making it more adjusted reality. To illustrate our proposed approach, case study estimates heat stress work uses data acquired from wearable devices. This automatically generates following indicators: (i) energy level wasted while performing physical activity, (ii) personalized measurement workload level, (iii) Occupational Heat Stress (OHS).