Avtor/Urednik		Todorovski, L; Džeroski, S; Kompare, B
Naslov		Automated modeling of phytoplankton growth using ecological domain knowledge
Tip		članek
Vir		In: Rajar R, Brebbia CA, editors. Water pollution 4: modeling, measuring and prediction. 4th international conference on water pollution; 1997 June; Bled. Southampton: Computational mechanics publications,
Leto izdaje		1997
Obseg		str. 532-42
Jezik		eng
Abstrakt		Using ecological domain knowledge, machine discovery systems can help human experts to generate models from measured data. In contrast with traditional modeling methods, which are used to identify parameter values of the model with prescribed structure, machine learning tools identify the structure of the model as well. In the paper, we present LAGRAMGE, an equation discovery system that uses context free grammars to define the space of possible model structures, and can also make use of domain specific background knowledge in the form of function definitions. We use LAGRAMGE to automate the modeling of phytoplankton growth in Lake Glumsoe, Denmark. The structure of the automaticly constructed model agrees with human experts expectations. The model can be successfully used for short-term prediction of the phytoplankton concentration.
Deskriptorji		PHYTOPLANKTON FRESH WATER COMPUTER SIMULATION ECOSYSTEM ECOLOGY ARTIFICIAL INTELLIGENCE