2022-12 | Estimation of cyanobacteria pigments in the main rivers of South Korea using spatial attention convolutional neural network with hyperspectral imagery | Hong, Seok Min; Cho, Kyung Hwa; Park, Sanghyun, et al | ARTICLE | 294 |
|
2022-09 | Predicting the salt adsorption capacity of different capacitive deionization electrodes using random forest | Park, Sanghun; Angeles, Anne Therese; Son, Moon, et al | ARTICLE | 26 |
|
2022-08 | Exploring potential machine learning application based on big data for prediction of wastewater quality from different full-scale wastewater treatment plants | Quang Viet Ly; Viet Hung Truong; Ji, Bingxuan, et al | ARTICLE | 20 |
|
2022-06 | Chemical accidents in freshwater: Development of forecasting system for drinking water resources | Kim, Soobin; Kim, Minjeong; Kim, Hyein, et al | ARTICLE | 79 |
|
2022-06 | Hierarchical deep learning model to simulate phytoplankton at phylum/ class and genus levels and zooplankton at the genus level | Baek, Sang-Soo; Jung, Eun-Young; Pyo, JongCheol, et al | ARTICLE | 41 |
|
2022-05 | Abundance and diversity of antibiotic resistance genes and bacterial communities in the western Pacific and Southern Oceans | Jang, Jiyi; Park, Jiyeon; Hwang, Chung Yeon, et al | ARTICLE | 119 |
|
2022-04 | A novel method for micropollutant quantification using deep learning and multi-objective optimization | Yun, Daeun; Kang, Daeho; Jang, Jiyi, et al | ARTICLE | 82 |
|
2022-04 | Optimal Band Selection for Airborne Hyperspectral Imagery to Retrieve a Wide Range of Cyanobacterial Pigment Concentration Using a Data-Driven Approach | Jang, Wonjin; Park, Yongeun; Pyo, JongCheol, et al | ARTICLE | 77 |
|
2022-04 | Dynamic calibration of phytoplankton blooms using the modified SWAT model | Lee, Jiye; Woo, So-Young; Kim, Yong-Won, et al | ARTICLE | 60 |
|
2022-04 | AI4Water v1.0: an open-source python package for modeling hydrological time series using data-driven methods | Abbas, Ather; Boithias, Laurie; Pachepsky, Yakov, et al | ARTICLE | 47 |
|
2022-02 | When river water meets seawater: Insights into primary marine aerosol production | Park, Jiyeon; Jang, Jiyi; Yoon, Young Jun, et al | ARTICLE | 231 |
|
2022-02 | Analysis of micropollutants in a marine outfall using network analysis and decision tree | Baek, Sang-Soo; Yun, Daeun; Pyo, JongCheol, et al | ARTICLE | 131 |
|
2022-02 | Interactions of E. coli with algae and aquatic vegetation in natural waters | Cho, Kyung Hwa; Wolny, Jennifer; Kase, Julie A., et al | ARTICLE | 46 |
|
2022-01 | Drone-borne sensing of major and accessory pigments in algae using deep learning modeling | Pyo, JongCheol; Hong, Seok Min; Jang, Jiyi, et al | ARTICLE | 109 |
|
2022-01 | Seawater battery desalination with a reverse osmosis membrane for simultaneous brine treatment and energy storage | Park, Sanghun; Kim, Namhyeok; Kim, Youngsik, et al | ARTICLE | 44 |
|
2021-12 | Modeling and evaluating performance of full-scale reverse osmosis system in industrial water treatment plant | Jeong, Kwanho; Son, Moon; Yoon, Nakyung, et al | ARTICLE | 231 |
|
2021-12 | Improving the performance of machine learning models for early warning of harmful algal blooms using an adaptive synthetic sampling method | Kim, Jin Hwi; Shin, Jae-Ki; Lee, Hankyu, et al | ARTICLE | 118 |
|
2021-12 | In-stream Escherichia coli modeling using high-temporal-resolution data with deep learning and process-based models | Abbas, Ather; Baek, Sangsoo; Silvera, Norbert, et al | ARTICLE | 109 |
|
2021-11 | Monitoring the vertical distribution of HABs using hyperspectral imagery and deep learning models | Hong, Seok Min; Baek,Sang-Soo; Yun, Daeun, et al | ARTICLE | 163 |
|
2021-11 | 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; Lê, Ngoc C., et al | ARTICLE | 170 |
|