The Discharge Forecasting of Multiple Monitoring Station for Humber River by Hybrid LSTM Models
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
The Discharge Forecasting of Multiple Monitoring Station for Humber River by Hybrid LSTM Models
Authors
Keywords
-
Journal
Water
Volume 14, Issue 11, Pages 1794
Publisher
MDPI AG
Online
2022-06-03
DOI
10.3390/w14111794
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Long short-term memory network-based user behavior analysis in virtual reality training system—a case study of the ship communication and navigation equipment training
- (2021) Bingchan Li et al. Arabian Journal of Geosciences
- A novel CNN-LSTM-based approach to predict urban expansion
- (2021) Wadii Boulila et al. Ecological Informatics
- An Efficient and Lightweight Deep Learning Model for Human Activity Recognition Using Smartphones
- (2021) Ankita et al. SENSORS
- Pipe Break Rate Assessment While Considering Physical and Operational Factors: A Methodology based on Global Positioning System and Data-Driven Techniques
- (2021) Yaser Amiri-Ardakani et al. WATER RESOURCES MANAGEMENT
- Application of ANN and HEC-RAS model for flood inundation mapping in lower Baro Akobo River Basin, Ethiopia
- (2021) Habtamu Tamiru et al. Journal of Hydrology-Regional Studies
- A review of wind speed and wind power forecasting with deep neural networks
- (2021) Yun Wang et al. APPLIED ENERGY
- Hourly road pavement surface temperature forecasting using deep learning models
- (2021) Sepideh Emami Tabrizi et al. JOURNAL OF HYDROLOGY
- Early detection model for the urban stream syndrome using specific stream power and regime theory
- (2021) K.M. MacKenzie et al. JOURNAL OF HYDROLOGY
- Flood hazards and factors influencing household flood perception and mitigation strategies in Pakistan
- (2020) Dilshad Ahmad et al. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
- Exploring a Long Short-Term Memory based Encoder-Decoder Framework for Multi-Step-Ahead Flood Forecasting
- (2020) I-Feng Kao et al. JOURNAL OF HYDROLOGY
- Receiving More Accurate Predictions for Longitudinal Dispersion Coefficients in Water Pipelines: Training Group Method of Data Handling Using Extreme Learning Machine Conceptions
- (2020) Farid Saberi-Movahed et al. WATER RESOURCES MANAGEMENT
- The Applicability of LSTM-KNN Model for Real-Time Flood Forecasting in Different Climate Zones in China
- (2020) Moyang Liu et al. Water
- Deep integro-difference equation models for spatio-temporal forecasting
- (2020) Andrew Zammit-Mangion et al. Spatial Statistics
- Complexity to Forecast Flood: Problem Definition and Spatiotemporal Attention LSTM Solution
- (2020) Yirui Wu et al. COMPLEXITY
- Interpretable spatio-temporal attention LSTM model for flood forecasting
- (2020) Yukai Ding et al. NEUROCOMPUTING
- A Comparative Study of Linear Stochastic with Nonlinear Daily River Discharge Forecast Models
- (2020) Hossein Bonakdari et al. WATER RESOURCES MANAGEMENT
- A comprehensive review of deep learning applications in hydrology and water resources
- (2020) Muhammed Sit et al. WATER SCIENCE AND TECHNOLOGY
- Network traffic classification using deep convolutional recurrent autoencoder neural networks for spatial–temporal features extraction
- (2020) Gianni D’Angelo et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- Deep learning neural networks for spatially explicit prediction of flash flood probability
- (2020) Mahdi Panahi et al. Geoscience Frontiers
- Predicting flood susceptibility using LSTM neural networks
- (2020) Zhice Fang et al. JOURNAL OF HYDROLOGY
- Deep Learning for Spatio-Temporal Data Mining: A Survey
- (2020) Senzhang Wang et al. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
- A Temperature-Scaling Approach for Projecting Changes in Short Duration Rainfall Extremes from GCM Data
- (2019) Ruben Dahm et al. Water
- A novel optimal-hybrid model for daily air quality index prediction considering air pollutant factors
- (2019) Qunli Wu et al. SCIENCE OF THE TOTAL ENVIRONMENT
- A multiscale and multivariate analysis of precipitation and streamflow variability in relation to ENSO, NAO and PDO
- (2019) D. Nalley et al. JOURNAL OF HYDROLOGY
- Runoff Prediction Method Based on Adaptive Elman Neural Network
- (2019) Chenming Li et al. Water
- Application of Long Short-Term Memory (LSTM) Neural Network for Flood Forecasting
- (2019) Le et al. Water
- A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm area
- (2019) Dieu Tien Bui et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Deep Random Subspace Learning: A Spatial-Temporal Modeling Approach for Air Quality Prediction
- (2019) Xiaotong Sun et al. Atmosphere
- A comprehensive comparison of four input variable selection methods for artificial neural network flow forecasting models
- (2019) E. Snieder et al. JOURNAL OF HYDROLOGY
- A spatio-temporal decomposition based deep neural network for time series forecasting
- (2019) Reza Asadi et al. APPLIED SOFT COMPUTING
- An ANN-based emulation modelling framework for flood inundation modelling: Application, challenges and future directions
- (2019) Haibo Chu et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Flash Flood Forecasting Based on Long Short-Term Memory Networks
- (2019) Tianyu Song et al. Water
- A modified F-test for evaluating model performance by including both experimental and simulation uncertainties
- (2018) Nathan Q. Sima et al. ENVIRONMENTAL MODELLING & SOFTWARE
- A trans-disciplinary review of deep learning research and its relevance for water resources scientists
- (2018) Chaopeng Shen WATER RESOURCES RESEARCH
- Dongting Lake Water Level Forecast and Its Relationship with the Three Gorges Dam Based on a Long Short-Term Memory Network
- (2018) Chen Liang et al. Water
- Short‐Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks
- (2018) Ata Akbari Asanjan et al. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
- Missing value imputation for the analysis of incomplete traffic accident data
- (2016) Rupam Deb et al. INFORMATION SCIENCES
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationPublish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn More