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The relative importance of water temperature and residence time in predicting cyanobacteria abundance in regulated rivers

Water research (Oxford), 2017-11, Vol.124, p.11-19

2017

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Projected climate change impact on cyanobacterial bloom phenology in temperate rivers based on temperature dependency

Water research (Oxford), 2024-02, Vol.249, p.120928-120928, Article 120928

2024

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Incorporation of feature engineering and attention mechanisms into deep learning models to develop an early warning system for harmful algal blooms

Journal of cleaner production, 2023-08, Vol.414, p.137564, Article 137564

2023

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Evaluating physico-chemical influences on cyanobacterial blooms using hyperspectral images in inland water, Korea

Water research (Oxford), 2017-12, Vol.126, p.319-328

2017

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Deep learning-based efficient drone-borne sensing of cyanobacterial blooms using a clique-based feature extraction approach

The Science of the total environment, 2024-02, Vol.912, p.169540-169540, Article 169540

2024

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Assessing the impacts of dam/weir operation on streamflow predictions using LSTM across South Korea

Scientific reports, 2023-06, Vol.13 (1), p.9296-9296, Article 9296

2023

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An interpretable machine learning method for supporting ecosystem management: Application to species distribution models of freshwater macroinvertebrates

Journal of environmental management, 2021-08, Vol.291, p.112719-112719, Article 112719

2021

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Deep learning-based retrieval of cyanobacteria pigment in inland water for in-situ and airborne hyperspectral data

Ecological indicators, 2020-03, Vol.110, p.105879, Article 105879

2020

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Forecasting Abrupt Depletion of Dissolved Oxygen in Urban Streams Using Discontinuously Measured Hourly Time‐Series Data

Water resources research, 2021-04, Vol.57 (4), p.n/a

2021

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Simultaneous feature engineering and interpretation: Forecasting harmful algal blooms using a deep learning approach

Water research (Oxford), 2022-05, Vol.215, p.118289-118289, Article 118289

2022

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Developing adverse outcome pathways on silver nanoparticle-induced reproductive toxicity via oxidative stress in the nematode Caenorhabditis elegans using a Bayesian network model

Nanotoxicology, 2018-11, Vol.12 (10), p.1182-1197

2018

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Effects of class imbalance on resampling and ensemble learning for improved prediction of cyanobacteria blooms

Ecological informatics, 2021-03, Vol.61, p.101202, Article 101202

2021

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New methodology of evaluation of best management practices performances for an agricultural watershed according to the climate change scenarios: A hybrid use of deterministic and decision support models

Ecological engineering, 2018-08, Vol.119, p.73-83

2018

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Machine learning-guided prediction of potential engineering targets for microbial production of lycopene

Bioresource technology, 2023-02, Vol.369, p.128455-128455, Article 128455

2023

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Validity evaluation of a machine-learning model for chlorophyll a retrieval using Sentinel-2 from inland and coastal waters

Ecological indicators, 2022-04, Vol.137, p.108737, Article 108737

2022

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Learning hierarchical Bayesian networks to assess the interaction effects of controlling factors on spatiotemporal patterns of fecal pollution in streams

The Science of the total environment, 2022-03, Vol.812, p.152520-152520, Article 152520

2022

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Hybrid model for daily streamflow and phosphorus load prediction

Water science and technology, 2023-08, Vol.88 (4), p.975-990

2023

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Mining web-based data to assess public response to environmental events

Environmental pollution (1987), 2015-03, Vol.198, p.97-99

2015

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Bayesian modeling approach for characterizing groundwater arsenic contamination in the Mekong River basin

Chemosphere (Oxford), 2016-01, Vol.143, p.50-56

2016

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Changes in zooplankton community in response to a shift from lentic to lotic conditions in a regulated river

Ecological informatics, 2023-11, Vol.77, p.102236, Article 102236

2023

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Simulating seasonal variability of phytoplankton in stream water using the modified SWAT model

Environmental modelling & software : with environment data news, 2019-12, Vol.122, p.104073, Article 104073

2019

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Machine learning-based prediction of harmful algal blooms in water supply reservoirs

Water quality research journal, 2022-11, Vol.57 (4), p.304-318

2022

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Data-driven models for predicting community changes in freshwater ecosystems: A review

Ecological informatics, 2023-11, Vol.77, p.102163, Article 102163

2023

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Modeling spatiotemporal bacterial variability with meteorological and watershed land-use characteristics

Water research (Oxford), 2016-09, Vol.100, p.306-315

2016

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A cross-scale view of N and P limitation using a Bayesian hierarchical model

Limnology and oceanography, 2016-11, Vol.61 (6), p.2276-2285

2016

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The relative importance of water temperature and residence time in predicting cyanobacteria abundance in regulated rivers

Projected climate change impact on cyanobacterial bloom phenology in temperate rivers based on temperature dependency

Incorporation of feature engineering and attention mechanisms into deep learning models to develop an early warning system for harmful algal blooms

Evaluating physico-chemical influences on cyanobacterial blooms using hyperspectral images in inland water, Korea

Deep learning-based efficient drone-borne sensing of cyanobacterial blooms using a clique-based feature extraction approach

Assessing the impacts of dam/weir operation on streamflow predictions using LSTM across South Korea

An interpretable machine learning method for supporting ecosystem management: Application to species distribution models of freshwater macroinvertebrates

Deep learning-based retrieval of cyanobacteria pigment in inland water for in-situ and airborne hyperspectral data

Forecasting Abrupt Depletion of Dissolved Oxygen in Urban Streams Using Discontinuously Measured Hourly Time‐Series Data

Simultaneous feature engineering and interpretation: Forecasting harmful algal blooms using a deep learning approach

Developing adverse outcome pathways on silver nanoparticle-induced reproductive toxicity via oxidative stress in the nematode Caenorhabditis elegans using a Bayesian network model

Effects of class imbalance on resampling and ensemble learning for improved prediction of cyanobacteria blooms

New methodology of evaluation of best management practices performances for an agricultural watershed according to the climate change scenarios: A hybrid use of deterministic and decision support models

Machine learning-guided prediction of potential engineering targets for microbial production of lycopene

Validity evaluation of a machine-learning model for chlorophyll a retrieval using Sentinel-2 from inland and coastal waters

Learning hierarchical Bayesian networks to assess the interaction effects of controlling factors on spatiotemporal patterns of fecal pollution in streams

Hybrid model for daily streamflow and phosphorus load prediction

Mining web-based data to assess public response to environmental events

Bayesian modeling approach for characterizing groundwater arsenic contamination in the Mekong River basin

Changes in zooplankton community in response to a shift from lentic to lotic conditions in a regulated river

Simulating seasonal variability of phytoplankton in stream water using the modified SWAT model

Machine learning-based prediction of harmful algal blooms in water supply reservoirs

Data-driven models for predicting community changes in freshwater ecosystems: A review

Modeling spatiotemporal bacterial variability with meteorological and watershed land-use characteristics

A cross-scale view of N and P limitation using a Bayesian hierarchical model

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