Forecast of environment systems using expert judgements: performance comparison between the possibilistic and the classical model

Jeremy Rohmer (1) , Eric Chojnacki (2)

1 BRGM - Bureau de Recherches Géologiques et Minières (BRGM)
2 IRSN/PSN-RES/SEMIA/LSMA - Laboratoire de statistique et des modélisations avancées

Expert judgment is widely used to inform forecasts (e.g. using the 5 th , 50 th and 95 th percentile of some variable of interest) for a large variety of applications related to environment systems. This task can rely on Cooke's classical model (CM) within the probabilistic framework, and consists in combining expert information after a preliminary step where experts are weighted using calibration and informativeness scores estimated using some seed questions for which the answers can be obtained. In the literature, an alternative model (PM) has been proposed using

Mots clés: Expert Calibration; Forecast Accuracy; Informativeness; Robustness; Probability; Possibility

Domaines: Informatique [cs]; Modélisation et simulation; Sciences de l'environnement; Environnement et Société; Sciences de l'environnement; Ingénierie de l'environnement; Statistiques [stat]; Applications [stat.AP]; Planète et Univers [physics]; Sciences de la Terre; Géologie appliquée; Sciences de l'Homme et Société; Méthodes et statistiques

Jeremy Rohmer, Eric Chojnacki. Forecast of environment systems using expert judgements: performance comparison between the possibilistic and the classical model. Environment Systems and Decisions, 2021, ⟨10.1007/s10669-020-09794-9⟩. ⟨hal-03105346⟩