22 May 2018
Research article | 22 May 2018
Framework for developing hybrid process-driven, artificial neural network and regression models for salinity prediction in river systems
Jason M. Hunter et al.
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15 citations as recorded by crossref.
- Water quality prediction using SWAT-ANN coupled approach N. Noori et al. 10.1016/j.jhydrol.2020.125220
- Statistical comparison between SARIMA and ANN’s performance for surface water quality time series prediction X. Wang et al. 10.1007/s11356-021-13086-3
- Water quality modeling in sewer networks: Review and future research directions Y. Jia et al. 10.1016/j.watres.2021.117419
- Short-term flood probability density forecasting using a conceptual hydrological model with machine learning techniques Y. Zhou et al. 10.1016/j.jhydrol.2021.127255
- The assessment of emerging data-intelligence technologies for modeling Mg+2 and SO4−2 surface water quality M. Jamei et al. 10.1016/j.jenvman.2021.113774
- An integrated framework of input determination for ensemble forecasts of monthly estuarine saltwater intrusion P. Lu et al. 10.1016/j.jhydrol.2021.126225
- Process‐Guided Deep Learning Predictions of Lake Water Temperature J. Read et al. 10.1029/2019WR024922
- Artificial neural network based hybrid modeling approach for flood inundation modeling S. Xie et al. 10.1016/j.jhydrol.2020.125605
- Deep learning, explained: Fundamentals, explainability, and bridgeability to process-based modelling S. Razavi 10.1016/j.envsoft.2021.105159
- ML-SWAN-v1: a hybrid machine learning framework for the concentration prediction and discovery of transport pathways of surface water nutrients B. Wang et al. 10.5194/gmd-13-4253-2020
- Enhanced Artificial Neural Networks for Salinity Estimation and Forecasting in the Sacramento-San Joaquin Delta of California S. Qi et al. 10.1061/(ASCE)WR.1943-5452.0001445
- A review of artificial neural network models for ambient air pollution prediction S. Cabaneros et al. 10.1016/j.envsoft.2019.06.014
- Introductory overview: Optimization using evolutionary algorithms and other metaheuristics H. Maier et al. 10.1016/j.envsoft.2018.11.018
- An ANN-based emulation modelling framework for flood inundation modelling: Application, challenges and future directions H. Chu et al. 10.1016/j.envsoft.2019.104587
- Space-time modelling of groundwater level and salinity F. Akter et al. 10.1016/j.scitotenv.2021.145865
Latest update: 29 Jun 2022