Predictive Process-based Modeling of Aquatic Ecosystems
Nina Vidmar, Nikola Simidjievski, Sašo Dzeroski Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia & Jozef Sefan Institute, Ljubljana, Slovenia & Jozef Stefan International Postgraduate School, Ljubljana, Slovenia
Abstract: In this paper, we consider the task of learning interpretable process-based models of dynamic systems. While most case studies have focused on the descriptive aspect of such models, we focus on the predictive aspect. We use multi-year data, considering it as a single consecutive dataset or as several one-year datasets. Additionally, we also investigate the effect of interpolation of sparse data on the learning process. We evaluate and then compare the considered approaches on the task of predictive modeling of phytoplankton dynamics in Lake Zürich.
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