Enhanced fuzzy evidential reasoning using an optimization approach for water quality monitoring

This paper proposes an enhanced fuzzy evidential reasoning (EFER) approach for decision making for means of water quality monitoring in the distribution networks under uncertain data and subjective knowledge. The proposed EFER approach can model epistemic uncertainties including ambiguity, interval-valued belief degrees and vagueness in information related to a complex system. Nonlinear optimization models that provide more information on the effect of interval-valued belief degrees in the final belief assessment are introduced to perform decision-making using an uncertain decision matrix. Due to modeling more facets of uncertainty, more information on the preference ranking of alternatives can be extracted. As a result, more distinctive preference between decision alternatives can be specified. The application of the proposed EFER approach is investigated through designing a decision support tool for water quality monitoring. Finally, the performance of the proposed framework is tested through online data that were available for a water distribution network.