A machine learning approach for early warning of cyanobacterial bloom outbreaks in a freshwater reservoir.

  title={A machine learning approach for early warning of cyanobacterial bloom outbreaks in a freshwater reservoir.},
  author={Yongeun Park and Hanbin Lee and Jae-Ki Shin and Kangmin Chon and Sunghwan Kim and Kyung Hwa Cho and Jin Hwi Kim and Sang-Soo Baek},
  journal={Journal of environmental management},

A Classification-Based Machine Learning Approach to the Prediction of Cyanobacterial Blooms in Chilgok Weir, South Korea

It can be concluded that it is possible to develop very accurate classification-based machine learning models with two features related to cyanobacterial blooms, and it is proved that these models could make efficient and effective models with a low number of inputs.

Machine learning predictions of chlorophyll-a in the Han river basin, Korea.

Using Artificial Intelligent to Model Predict the Biological Resilience With an Emphasis on Population of cyanobacteria in Jajrood River in The Eastern Tehran, Iran

Prediction of bio-resilience in water resources such as rivers is important for better management of land-use systems and water resources. This study has proposed the use of artificial intelligent

Cyanobacteria blue-green algae prediction enhancement using hybrid machine learning–based gamma test variable selection and empirical wavelet transform

Evaluated machine learning models for modelling cyanobacteria blue-green algae at two rivers located in the USA show that good predictive accuracy was obtained using the RFR model and the ANN and RFR were found to be more accurate compared to the ELM and RVFL models, exhibiting high numerical performances.



A novel single-parameter approach for forecasting algal blooms.

A study on the management and improvement of alert system according to algal bloom in the Daecheong Reservoir

Following the industrialization and urbanization in Korea, algal bloom causes aesthetic displeasure and many other problems such as taste and odor, coloration, scum, increase in pH, filter-bed

Probabilistic prediction of cyanobacteria abundance in a Korean reservoir using a Bayesian Poisson model

There have been increasing reports of harmful algal blooms (HABs) worldwide. However, the factors that influence cyanobacteria dominance and HAB formation can be site‐specific and idiosyncratic,