Naslov
Use of machine learning for determining phytoplankton dynamic on station RV001 in front of Rovinj (northern Adriatic)

Autori
Volf, Goran ; Kompare, Boris ; Ožanić, Nevenka

Izvornik
Engineering review : znanstveni časopis za nove tehnologije u strojarstvu, brodogradnji i elektrotehnici (1330-9587) 34 (2014); 181-187

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Northern Adriatic ; Machine learning ; Phytoplankton

Sažetak
The paper describes the use of machine learning for modeling phytoplankton on data from station RV001 in front of Rovinj which well represents the main processes in the open northern Adriatic (NA). NA is the shallowest, and also one of the most productive areas in the Adriatic Sea, as well as in the entire Mediterranean. In order to contribute to the understanding of phytoplankton dynamic in the NA, on data covering physical, biological and chemical parameters machine learning (ML) techniques were used. The final result is the construction of the models in the form of regression and model trees, respectively ; there were constructed models that explain the dynamics of phytoplankton concentrations on mentioned station as a result of independent environmental variables. Models in an affordable way combine and show knowledge collected by measurements during 35 year period, which contributes to a better understanding of the functioning of the NA ecosystem.

Izvorni jezik
Engleski

Znanstvena područja
Građevinarstvo

POVEZANOST RADA