公開日期 | 標題 | 作者 | 來源出版物 | scopus | WOS | 全文 |
2024 | Advancing climate-resilient flood mitigation: Utilizing transformer-LSTM for water level forecasting at pumping stations | Kow, Pu Yun; Liou, Jia Yi; Yang, Ming Ting; Lee, Meng Hsin; Chang, Li Chiu; FI-JOHN CHANG | Science of the Total Environment | | | |
2022 | Deep neural networks for spatiotemporal PM<inf>2.5</inf> forecasts based on atmospheric chemical transport model output and monitoring data | Kow, Pu Yun; Chang, Li Chiu; Lin, Chuan Yao; Chou, Charles C.K.; FI-JOHN CHANG | Environmental Pollution | 27 | 23 | |
2023 | Develop a hybrid machine learning model for promoting microbe biomass production | Kow, Pu Yun; Lu, Mei Kuang; Lee, Meng Hsin; Lu, Wei Bin; FI-JOHN CHANG | Bioresource Technology | 3 | 2 | |
2023 | High-spatiotemporal-resolution PM2.5 forecasting by hybrid deep learning models with ensembled massive heterogeneous monitoring data | Wu, Kuan Yen; Hsia, I. Wen; Kow, Pu Yun; Chang, Li Chiu; FI-JOHN CHANG | Journal of Cleaner Production | 0 | | |
2022 | Integrate deep learning and physically-based models for multi-step-ahead microclimate forecasting | Kow, Pu Yun; Lee, Meng Hsin; Sun, Wei; Yao, Ming Hwi; FI-JOHN CHANG | Expert Systems with Applications | 4 | 3 | |
2024 | Watershed groundwater level multistep ahead forecasts by fusing convolutional-based autoencoder and LSTM models | Kow, Pu Yun; Liou, Jia Yi; Sun, Wei; Chang, Li Chiu; FI-JOHN CHANG | Journal of Environmental Management | 2 | | |