A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Modelling and prediction of phyto‐ and zooplankton dynamics in Lake Kasumigaura by artificial neural networks
An artificial neural network model was developed for Lake Kasumigaura to predict timing and magnitudes for chlorophyll a, five species of blue‐green algae and three zooplankton groups. The model was trained by 8 years of limnological time series and validated by two independent years. The validation showed the potential of neural networks as predictive tools for highly non‐linear phenomena such as blue‐green algal blooms in freshwater lakes.
Modelling and prediction of phyto‐ and zooplankton dynamics in Lake Kasumigaura by artificial neural networks
An artificial neural network model was developed for Lake Kasumigaura to predict timing and magnitudes for chlorophyll a, five species of blue‐green algae and three zooplankton groups. The model was trained by 8 years of limnological time series and validated by two independent years. The validation showed the potential of neural networks as predictive tools for highly non‐linear phenomena such as blue‐green algal blooms in freshwater lakes.
Modelling and prediction of phyto‐ and zooplankton dynamics in Lake Kasumigaura by artificial neural networks
Recknagel, Friedrich (author) / Fukushima, Takehiko (author) / Hanazato, Takayuki (author) / Takamura, Noriko (author) / Wilson, Hugh (author)
Lakes & Reservoirs: Research & Management ; 3 ; 123-133
1998-06-01
11 pages
Article (Journal)
Electronic Resource
English
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