Temporal multiresolution analysis for a quantitative/qualitative interpretation of complex dynamic processes
Résumé
The paper describes a qualitative reasoning approach aimed at representing and interpreting a dynamic process evolution. The problem specifically addressed is the presence of multiple timescales in complex systems. Definitions of temporal granularity as well as related concepts are provided. For the representation of a single process, a segmentation and abstraction method is described. the identification of dynamic features at any level of abstraction then supplies a help to better choose relevant sampling frequencies of the simulated process and helps in interpreting its outputs. An example is given for a complex crop growth model, whose interpretation is tested against expert knowledge.