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Predicting the Water Level Fluctuation in an Alpine Lake Using Physically Based, Artificial Neural Network, and Time Series Forecasting Models
Accurate prediction of water level fluctuation is important in lake management due to its significant impacts in various aspects. This study utilizes four model approaches to predict water levels inExpand
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Genetic algorithm and fuzzy neural networks combined with the hydrological modeling system for forecasting watershed runoff discharge
  • C. Young, W. Liu, C. Chung
  • Environmental Science, Computer Science
  • Neural Computing and Applications
  • 1 October 2015
TLDR
This study utilizes three model approaches to predict runoff discharge in the Laonong Creek basin in southern Taiwan: the hydrological engineering center hydrologogical modeling system (HEC-HMS) model, a genetic algorithm neural network (GANN) and an adaptive neuro-fuzzy inference system approach (ANFIS). Expand
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Modeling fecal coliform contamination in a tidal Danshuei River estuarine system.
A three-dimensional fecal coliform transport model was developed and incorporated into a hydrodynamic model to obtain a better understanding of local microbiological water quality in the tidalExpand
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Evaluation of marine outfall with three-dimensional hydrodynamic and water quality modeling
Numerical models are often used to evaluate the potential impact of human alternation of natural water bodies and to help the design of the alternation to mitigate its impacts. In the past decade,Expand
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An efficient and accurate non-hydrostatic model with embedded Boussinesq-type like equations for surface wave modeling
A novel approach that embeds the Boussinesq-type like equations into an implicit non-hydrostatic model (NHM) is developed. Instead of using an integration approach, Boussinesq-type like equationsExpand
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Efficient Nonhydrostatic Modeling of Surface Waves from Deep to Shallow Water
An efficient nonhydrostatic model with the embedded Boussinesq-type like equations at the free surface is presented to simulate surface waves from shallow to deep water. The new free-surfaceExpand
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Characteristics of the RAW-Filtered Leapfrog Time-Stepping Scheme in the Ocean General Circulation Model
The Robert‐Asselin‐Williams (RAW) filtered leapfrog scheme is implemented and tested in the Taiwan multiscalecommunityoceanmodel(TIMCOM).ThecharacteristicsoftheRAWfilterarecarefullyexamined throughExpand
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A physically based and machine learning hybrid approach for accurate rainfall-runoff modeling during extreme typhoon events
TLDR
A novel hybrid model which integrates the outputs of physically based hydrologic modeling system into support vector machine is developed to predict hourly runoff discharges in Chishan Creek basin in southern Taiwan. Expand
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Prediction and modelling of rainfall–runoff during typhoon events using a physically-based and artificial neural network hybrid model
Abstract The accurate prediction of hourly runoff discharge in a watershed during heavy rainfall events is of critical importance for flood control and management. This study predicts n-h-aheadExpand
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An efficient curvilinear non‐hydrostatic model for simulating surface water waves
An efficient curvilinear non-hydrostatic free surface model is developed to simulate surface water waves in horizontally curved boundaries. The generalized curvilinear governing equations are solvedExpand
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