Enhancing Bayes' Probabilistic Decision Support with a Fuzzy Approach

Abstract

This paper proposes an enhancement to a traditional decision making approach based on Bayes' mathematical theory. The objective is to develop an effective decision support under conditions of uncertainty while exploiting low measured or audited information. The case study will be the application of alternative interventions to buildings in order to improve their energy consumption. A fuzzy approach is examined which attempts to formulate a 'fair' membership function in order to produce weights and assist Bayes' method.