093 / 1 |
Fuzzy exemplar-based inference system for flood forecasting
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094 / 1 |
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093 / 2 |
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094 / 2 |
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096 / 2 |
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095 / 2 |
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098 / 1 |
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092 / 1 |
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091 / 1 |
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2016-12-21 |
098 / 2 |
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098 / 2 |
Clustering-based hybrid inundation model for forecasting flood inundation depths
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2014-08-15 |
092 / 2 |
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097 / 2 |
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2017-01-11 |
089 / 2 |
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098 / 1 |
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2017-03-22 |
082 / 1 |
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099 / 2 |
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100 / 1 |
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2014-08-15 |
101 / 1 |
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2013-04-11 |
102 / 1 |
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2015-12-03 |
101 / 2 |
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102 / 2 |
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103 / 1 |
Regional flood inundation nowcast using hybrid SOM and dynamic neural networks
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104 / 1 |
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105 / 1 |
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105 / 1 |
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107 / 1 |
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107 / 1 |
Building an intelligent Hydroinformatics Integration platform for a regional flood inundation warning systems
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2023-07-17 |
106 / 1 |
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108 / 1 |
AI-based design of urban stormwater detention facilities accounting for carryover storage
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2021-03-15 |
107 / 2 |
Modeling and investigating the mechanisms of groundwater level variation in the Jhuoshui River Basin of Central Taiwan
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2021-03-13 |
108 / 2 |
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108 / 2 |
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2024-07-22 |
109 / 1 |
Explore Regional PM2.5 Features and Compositions Causing Health Effects in Taiwan
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109 / 2 |
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Regional Inundation Forecasting Using Machine Learning Techniques with the Internet of Things
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108 / 2 |
Explore a Multivariate Bayesian Uncertainty Processor driven by artificial neural networks for probabilistic PM2.5 forecasting
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Spatial-temporal flood inundation nowcasts by fusing machine learning methods and principal component analysis
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2024-07-02 |
111 / 1 |
Deep neural networks for spatiotemporal PM2.5 forecasts based on atmospheric chemical transport model output and monitoring data
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110 / 1 |
Real-time image-based air quality estimation by deep learning neural networks
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2023-07-31 |
110 / 2 |
A Combined O/U-Tube Oscillatory Water Tunnel for Fluid Flow and Sediment Transport Studies: The Hydrodynamics and Genetic Algorithm
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2023-07-31 |
112 / 1 |
A flood Impact-Based forecasting system by fuzzy inference techniques
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2024-07-02 |
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High-spatiotemporal-resolution PM2.5 forecasting by hybrid deep learning models with ensembled massive heterogeneous monitoring data
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Watershed groundwater level multistep ahead forecasts by fusing convolutional-based autoencoder and LSTM models
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