Prediction and elucidation of population dynamics of the blue-green algae Microcystis aeruginosa and the diatom Stepanodiscus hantzschii in the Nakdong River-reservoir system (South Korea) by a recurrent artificial neural network

Application of Machine Learning for eutrophication analysis and algal bloom prediction in an urban river: A 10-year study of the Han River, South Korea

Ly, Quang Viet
Nguyen, Xuan Cuong
L??, Ngoc C.
Truong, Tien-Dung
Hoang, Thu-Huong T.
Park, Tae Jun
Maqbool, Tahir
Pyo, JongCheol
Cho, Kyung Hwa
Lee, Kwang-Sik
Hur, Jin

November 2021

The increasing release of nutrients to aquatic environments has led to great concern regarding eutro...

Predicting eutrophication effects in the Burrinjuck Reservoir (Australia) by means of the deterministic model SALMO and the recurrent neural network model ANNA

Walter, M.
Recknagel, F.
Carpenter, C.
Bormans, M.

January 2001

Artificial neural network approach to population dynamics of Harmful Algal Blooms in Alfacs Bay (NW Mediterranean): Case studies of Karlodinium and Pseudo-nitzschia

Guallar, C.
Fernández-Tejedor, Margarita
Delgado, Maximino
Diogène, Jorge

November 2013

Symposium on Integrating New Advances in Mediterranean Oceanography and Marine Biology, 26-29 Novemb...

Elucidation of hypothetical relationships between habitat conditions and macroinvertebrate assemblages in freshwater streams by artificial neural networks

Hoang, H.
Recknagel, F.
Marshall, J.
Choy, S.

January 2003

Originally published as Chapter 9 in the 1st edition (2003), this chapter appears unchanged in the 2...

Predictive function and rules for population dynamics of Micyocystis aeruginosa in the regulated Nakdong River (South Korea), discovered by evolutionary algorithms

Kim, B.
Cao, H.
Jeong, K.
Recknagel, F.
Joo, G.

January 2007

Artificial Neural Network (ANN) Modeling Analysis of Algal Blooms in an Estuary with Episodic and Anthropogenic Freshwater Inputs

Sangjun Park
Yongsik Sin

July 2021

The Youngsan River estuary, located on the southwest coast of South Korea, has transitioned from a n...

Elucidation and short-term forecasting of microcystin concentrations in Lake Suwa (Japan) by means of artificial neural networks and evolutionary algorithms

Chan, W.
Recknagel, F.
Cao, H.
Park, H.

January 2007

SUMMARY

Guoxiang Hou
Hongbin Li
Friedrich Recknagel
Lirong Song

October 2015

The paper demonstrates the nonstationarity of algal population behaviors by analyzing the historical...

Four Major South Korea’s Rivers Using Deep Learning Models

Sangmok Lee
Donghyun Lee

June 2018

Harmful algal blooms are an annual phenomenon that cause environmental damage, economic losses, and ...

Improved Prediction of Harmful Algal Blooms in Four Major South Korea’s Rivers Using Deep Learning Models

Sangmok Lee

June 2018

Harmful algal blooms are an annual phenomenon that cause environmental damage, economic losses, and ...

Unravelling and forecasting algal population dynamics in two lakes different in morphometry and eutrophication by neural and evolutionary computation

Recknagel, F.
Cao, H.
Kim, B.
Takamura, N.
Welk, A.

January 2006

Korea: explanations based on evolutionary computation

January 2016

1. An ecological model was developed using genetic programming (GP) to predict the time-series dynam...

Comparison of models for predicting the changes in phytoplankton community composition in the receiving water system of an inter basin water transfer project

Zeng, Qinghui
Liu, Yi
Zhao, Hongtao
Sun, Mingdong
Li, Xuyong

April 2017

Inter-basin water transfer projects might cause complex hydro-chemical and biological variation in t...

Using the moving window incorporated neural network to forecast the population behavior of Nostocales spp. in the River Darling, Australia

Hou, G.
Li, H.
Recknagel, F.
Song, L.

January 2007

The paper demonstrates the nonstationarity of algal population behaviors by analyzing the historical...

Artificial neural network approach to population dynamics of harmful algal blooms in Alfacs Bay (NW Mediterranean): Case studies of Karlodinium and Pseudo-nitzschia

Guallar, C.
Delgado, Maximino
Diogène, Jorge
Fernández-Tejedor, Margarita

October 2016

14 pages, 10 figures, 7 tables, supplementary data http://dx.doi.org/10.1016/j.ecolmodel.2016.07.009...

Application of Machine Learning for eutrophication analysis and algal bloom prediction in an urban river: A 10-year study of the Han River, South Korea

Ly, Quang Viet
Nguyen, Xuan Cuong
L??, Ngoc C.
Truong, Tien-Dung
Hoang, Thu-Huong T.
Park, Tae Jun
Maqbool, Tahir
Pyo, JongCheol
Cho, Kyung Hwa
Lee, Kwang-Sik
Hur, Jin

November 2021

The increasing release of nutrients to aquatic environments has led to great concern regarding eutro...

Predicting eutrophication effects in the Burrinjuck Reservoir (Australia) by means of the deterministic model SALMO and the recurrent neural network model ANNA

Walter, M.
Recknagel, F.
Carpenter, C.
Bormans, M.

January 2001

Artificial neural network approach to population dynamics of Harmful Algal Blooms in Alfacs Bay (NW Mediterranean): Case studies of Karlodinium and Pseudo-nitzschia

Guallar, C.
Fernández-Tejedor, Margarita
Delgado, Maximino
Diogène, Jorge

November 2013

Symposium on Integrating New Advances in Mediterranean Oceanography and Marine Biology, 26-29 Novemb...

Elucidation of hypothetical relationships between habitat conditions and macroinvertebrate assemblages in freshwater streams by artificial neural networks

Hoang, H.
Recknagel, F.
Marshall, J.
Choy, S.

January 2003

Originally published as Chapter 9 in the 1st edition (2003), this chapter appears unchanged in the 2...

Predictive function and rules for population dynamics of Micyocystis aeruginosa in the regulated Nakdong River (South Korea), discovered by evolutionary algorithms

Kim, B.
Cao, H.
Jeong, K.
Recknagel, F.
Joo, G.

January 2007

Artificial Neural Network (ANN) Modeling Analysis of Algal Blooms in an Estuary with Episodic and Anthropogenic Freshwater Inputs

Sangjun Park
Yongsik Sin

July 2021

The Youngsan River estuary, located on the southwest coast of South Korea, has transitioned from a n...

Elucidation and short-term forecasting of microcystin concentrations in Lake Suwa (Japan) by means of artificial neural networks and evolutionary algorithms

Chan, W.
Recknagel, F.
Cao, H.
Park, H.

January 2007

SUMMARY

Guoxiang Hou
Hongbin Li
Friedrich Recknagel
Lirong Song

October 2015

The paper demonstrates the nonstationarity of algal population behaviors by analyzing the historical...

Four Major South Korea’s Rivers Using Deep Learning Models

Sangmok Lee
Donghyun Lee

June 2018

Harmful algal blooms are an annual phenomenon that cause environmental damage, economic losses, and ...

Improved Prediction of Harmful Algal Blooms in Four Major South Korea’s Rivers Using Deep Learning Models

Sangmok Lee

June 2018

Harmful algal blooms are an annual phenomenon that cause environmental damage, economic losses, and ...

Unravelling and forecasting algal population dynamics in two lakes different in morphometry and eutrophication by neural and evolutionary computation

Recknagel, F.
Cao, H.
Kim, B.
Takamura, N.
Welk, A.

January 2006

Korea: explanations based on evolutionary computation

January 2016

1. An ecological model was developed using genetic programming (GP) to predict the time-series dynam...

Comparison of models for predicting the changes in phytoplankton community composition in the receiving water system of an inter basin water transfer project

Zeng, Qinghui
Liu, Yi
Zhao, Hongtao
Sun, Mingdong
Li, Xuyong

April 2017

Inter-basin water transfer projects might cause complex hydro-chemical and biological variation in t...

Using the moving window incorporated neural network to forecast the population behavior of Nostocales spp. in the River Darling, Australia

Hou, G.
Li, H.
Recknagel, F.
Song, L.

January 2007

The paper demonstrates the nonstationarity of algal population behaviors by analyzing the historical...

Artificial neural network approach to population dynamics of harmful algal blooms in Alfacs Bay (NW Mediterranean): Case studies of Karlodinium and Pseudo-nitzschia

Guallar, C.
Delgado, Maximino
Diogène, Jorge
Fernández-Tejedor, Margarita

October 2016

14 pages, 10 figures, 7 tables, supplementary data http://dx.doi.org/10.1016/j.ecolmodel.2016.07.009...

Application of Machine Learning for eutrophication analysis and algal bloom prediction in an urban river: A 10-year study of the Han River, South Korea

Ly, Quang Viet
Nguyen, Xuan Cuong
L??, Ngoc C.
Truong, Tien-Dung
Hoang, Thu-Huong T.
Park, Tae Jun
Maqbool, Tahir
Pyo, JongCheol
Cho, Kyung Hwa
Lee, Kwang-Sik
Hur, Jin

November 2021

The increasing release of nutrients to aquatic environments has led to great concern regarding eutro...

Predicting eutrophication effects in the Burrinjuck Reservoir (Australia) by means of the deterministic model SALMO and the recurrent neural network model ANNA

Walter, M.
Recknagel, F.
Carpenter, C.
Bormans, M.

January 2001

Artificial neural network approach to population dynamics of Harmful Algal Blooms in Alfacs Bay (NW Mediterranean): Case studies of Karlodinium and Pseudo-nitzschia

Guallar, C.
Fernández-Tejedor, Margarita
Delgado, Maximino
Diogène, Jorge

November 2013

Symposium on Integrating New Advances in Mediterranean Oceanography and Marine Biology, 26-29 Novemb...

Prediction and elucidation of population dynamics of the blue-green algae Microcystis aeruginosa and the diatom Stepanodiscus hantzschii in the Nakdong River-reservoir system (South Korea) by a recurrent artificial neural network

Abstract

Extracted data

Prediction and elucidation of population dynamics of the blue-green algae Microcystis aeruginosa and the diatom Stepanodiscus hantzschii in the Nakdong River-reservoir system (South Korea) by a recurrent artificial neural network

Abstract

Extracted data

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