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Document type:
Bachelorarbeit 
Author(s):
Simon Zocholl 
Title:
Development of Recurrent Neural Network Architectures for Hydrological Time Series Forecasting 
Translated title:
Entwicklung Rekurrenter Neuronaler Netzwerk Architekturen für Hydrologische Zeitfolgen Vorhersagen 
Abstract:
Precise prediction of the future streamflow is an important step when building an effective flood or low-flow warning system. Over the years, hydrologists have developed and used complex process-based hydrological models to solve the streamflow prediction task. However, recently a specific type of data-driven model, more precisely Recurrent Neural Networks (RNNs), have shown impressive results in many sequence predictions and time series forecasting tasks. These data-driven models are comparativ...    »
 
Supervisor:
Univ.-Prof. Dr. Hans-Joachim Bungartz 
Advisor:
Ivana Jovanovic Buha 
Referee:
Dr. Wolfgang Kurtz 
Year:
2021 
Quarter:
2. Quartal 
Year / month:
2021-04 
Month:
Apr 
Language:
en 
University:
Techinische Universität München 
Faculty:
Fakultät für Informatik