Representing Fuzzy Temporal Knowledge

Many systems collect vast data over time, which is used for critical tasks like diagnosis, surveillance, resource management, planning and forecasting. To effectively use the historical data for these purposes, it is important to comprehend its significant structure by identifying the presence and characteristics of specific patterns. We describe a fuzzy logical notation, enhanced with facilities for expressing approximate temporal patterns, to build compositional and abstract models of syntactic structure of patterns. We describe how a temporal database can provide an interpretation for a given formula in this logic. We describe a fuzzy version of Allen’s interval algebra as meta-temporal facilities to specify intervals where a given fuzzy temporal formula shows a significant presence and to describe relationships between intervals. We illustrate this logic to describe fuzzy temporal patterns over temporal databases and to express expert knowledge about temporal phenomena; we use the problem of identifying failing and potentially failing banks from their operational data.