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Prediction of Water Level and Water Quality Using a CNN-LSTM Combined Deep Learning Approach

Water (Basel), 2020-12, Vol.12 (12), p.3399

2020

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Characterization of micropollutants in urban stormwater using high-resolution monitoring and machine learning

Water research (Oxford), 2023-05, Vol.235, p.119865-119865, Article 119865

2023

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Optimizing low impact development (LID) for stormwater runoff treatment in urban area, Korea: Experimental and modeling approach

Water research (Oxford), 2015-12, Vol.86, p.122-131

2015

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Recent Advances in Touch Sensors for Flexible Wearable Devices

Sensors (Basel, Switzerland), 2022-06, Vol.22 (12), p.4460

2022

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Potential inhibition of the harmful dinoflagellate Cochlodinium (= Margalefidinium) polykrikoides by the intrusion of Changjiang diluted water into Korea coastal waters

Ecological indicators, 2022-06, Vol.139, p.108924, Article 108924

2022

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Optimizing Agricultural Best Management Practices in a Lake Erie Watershed

Journal of the American Water Resources Association, 2017-12, Vol.53 (6), p.1281-1292

2017

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Deep learning-based algorithms for long-term prediction of chlorophyll-a in catchment streams

Journal of hydrology (Amsterdam), 2023-11, Vol.626, p.130240, Article 130240

2023

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Deep Learning for Simulating Harmful Algal Blooms Using Ocean Numerical Model

Frontiers in Marine Science, 2021-10, Vol.8

2021

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Cyanobacteria cell prediction using interpretable deep learning model with observed, numerical, and sensing data assemblage

Water research (Oxford), 2021-09, Vol.203, p.117483, Article 117483

2021

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Using convolutional neural network for predicting cyanobacteria concentrations in river water

Water research (Oxford), 2020-11, Vol.186, p.116349-116349, Article 116349

2020

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Sensitivity Analysis and Optimization of a Radiative Transfer Numerical Model for Turbid Lake Water

Remote sensing (Basel, Switzerland), 2021-02, Vol.13 (4), p.709

2021

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Profiling emerging micropollutants in urban stormwater runoff using suspect and non-target screening via high-resolution mass spectrometry

Chemosphere (Oxford), 2024-03, Vol.352, p.141402-141402, Article 141402

2024

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Data assimilation for urban stormwater and water quality simulations using deep reinforcement learning

Journal of hydrology (Amsterdam), 2023-09, Vol.624, p.129973, Article 129973

2023

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Optimizing Semi-Analytical Algorithms for Estimating Chlorophyll-a and Phycocyanin Concentrations in Inland Waters in Korea

Remote sensing (Basel, Switzerland), 2017-06, Vol.9 (6), p.542

2017

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Improving the performance of machine learning models for early warning of harmful algal blooms using an adaptive synthetic sampling method

Water research (Oxford), 2021-12, Vol.207, p.117821-117821, Article 117821

2021

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Deep neural networks for modeling fouling growth and flux decline during NF/RO membrane filtration

Journal of membrane science, 2019-10, Vol.587, p.117164, Article 117164

2019

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A novel water quality module of the SWMM model for assessing low impact development (LID) in urban watersheds

Journal of hydrology (Amsterdam), 2020-07, Vol.586, p.124886, Article 124886

2020

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Replacing the internal standard to estimate micropollutants using deep and machine learning

Water research (Oxford), 2021-01, Vol.188, p.116535, Article 116535

2021

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Synergistic effects of tungstate trioxide hemihydrate decorated reduced graphene oxide for the adsorption of heavy metals and dyes and postliminary application in supercapacitor device

Journal of cleaner production, 2023-09, Vol.418, p.138067, Article 138067

2023

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Developing a deep learning model for the simulation of micro-pollutants in a watershed

Journal of cleaner production, 2021-06, Vol.300, p.126858, Article 126858

2021

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Chemical accidents in freshwater: Development of forecasting system for drinking water resources

Journal of hazardous materials, 2022-06, Vol.432, p.128714-128714, Article 128714

2022

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Monitoring the vertical distribution of HABs using hyperspectral imagery and deep learning models

The Science of the total environment, 2021-11, Vol.794, p.148592-148592, Article 148592

2021

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Analysis of micropollutants in a marine outfall using network analysis and decision tree

The Science of the total environment, 2022-02, Vol.806 (Pt 4), p.150938-150938, Article 150938

2022

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

Journal of environmental management, 2021-06, Vol.288, p.112415, Article 112415

2021

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A novel method for micropollutant quantification using deep learning and multi-objective optimization

Water research (Oxford), 2022-04, Vol.212, p.118080-118080, Article 118080

2022

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Prediction of Water Level and Water Quality Using a CNN-LSTM Combined Deep Learning Approach

Characterization of micropollutants in urban stormwater using high-resolution monitoring and machine learning

Optimizing low impact development (LID) for stormwater runoff treatment in urban area, Korea: Experimental and modeling approach

Recent Advances in Touch Sensors for Flexible Wearable Devices

Potential inhibition of the harmful dinoflagellate Cochlodinium (= Margalefidinium) polykrikoides by the intrusion of Changjiang diluted water into Korea coastal waters

Optimizing Agricultural Best Management Practices in a Lake Erie Watershed

Deep learning-based algorithms for long-term prediction of chlorophyll-a in catchment streams

Deep Learning for Simulating Harmful Algal Blooms Using Ocean Numerical Model

Cyanobacteria cell prediction using interpretable deep learning model with observed, numerical, and sensing data assemblage

Using convolutional neural network for predicting cyanobacteria concentrations in river water

Sensitivity Analysis and Optimization of a Radiative Transfer Numerical Model for Turbid Lake Water

Profiling emerging micropollutants in urban stormwater runoff using suspect and non-target screening via high-resolution mass spectrometry

Data assimilation for urban stormwater and water quality simulations using deep reinforcement learning

Optimizing Semi-Analytical Algorithms for Estimating Chlorophyll-a and Phycocyanin Concentrations in Inland Waters in Korea

Improving the performance of machine learning models for early warning of harmful algal blooms using an adaptive synthetic sampling method

Deep neural networks for modeling fouling growth and flux decline during NF/RO membrane filtration

A novel water quality module of the SWMM model for assessing low impact development (LID) in urban watersheds

Replacing the internal standard to estimate micropollutants using deep and machine learning

Synergistic effects of tungstate trioxide hemihydrate decorated reduced graphene oxide for the adsorption of heavy metals and dyes and postliminary application in supercapacitor device

Developing a deep learning model for the simulation of micro-pollutants in a watershed

Chemical accidents in freshwater: Development of forecasting system for drinking water resources

Monitoring the vertical distribution of HABs using hyperspectral imagery and deep learning models

Analysis of micropollutants in a marine outfall using network analysis and decision tree

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

A novel method for micropollutant quantification using deep learning and multi-objective optimization

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