Joint Application of Analytic Hierarchy Process (AHP) and Bayesian Networks (BN) to Electromagnetic Environment Effects (E3) Assessment

Abstract

The electromagnetic environment effect (E3) mainly concerns the risk of the system function impacted by the exterior intense radio signal. The E3 assessments try to capture the potential weakness of systems with tests, computations and estimations. The method of Analytic Hierarchy Process (AHP) is helpful to divide the large systems into smaller parts. On the other hand, AHP has disadvantages of subjectivity and loss of the original connectivity. The Bayesian Networks (BN) from the field of statistical causality or explainable artificial intelligence (AI) can absorb not only the advantages of AHP, but also permit the objective data obtained by the test and computations. So the primary trial indicates that the BN can remedy these shortcomings. And the joint Application of AHP) and BN provide us a whole hierarchical view of the E3 assessment activities.