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Identification and estimation of continuous-time, data-based mechanistic (DBM) models for environmental systems
2006
Environmental Modelling & Software
Initially, the paper provides an introduction to the main aspects of existing timedomain methods for identifying linear continuous-time models from discrete-time data and shows how one of these methods has been applied to the identification and estimation of a model for the transportation and dispersion of a pollutant in a river. It then introduces a widely applicable class of new, nonlinear, State-Dependent Parameter (SDP) models. Finally, the paper describes how this SDP approach has been
doi:10.1016/j.envsoft.2005.05.007
fatcat:housujxcu5d7tj5fjxrafwaep4