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Recurrent Neural Network (RNN) For Stream Flow Forecasting

FYP Sem 2 2019/2020

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Main Author: Alkatheri Ali Karama Gumaan
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Published: 2023
Subjects:
Stream Flow
Forecast
Artificial Neural Networks (ANN)
Long Short Term Memory (LSTM)
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spelling my.uniten.dspace-214672023-05-04T17:36:46Z Recurrent Neural Network (RNN) For Stream Flow Forecasting Alkatheri Ali Karama Gumaan Stream Flow Forecast Artificial Neural Networks (ANN) Long Short Term Memory (LSTM) FYP Sem 2 2019/2020 The increase in stream flow is an important issue since it can be used as a flood warning indicator. The stream flow of a river depends on variables such as rainfall, runoff and surface wind. The primary objective of this study is to find a reliable method to predict the stream flow of the Kuantan River in Malaysia. In this study, applied using two different input which are daily stream flow and daily rainfall. In this study, the data of the stream flow and rainfall were obtained for a duration of nine years and . Two models were used in this study were used to analyze the data, which are Long Short Term Memory (LSTM) and Artificial Neural Networks (ANN) models. The result demonstrates that the Long Short Term Memory is superior to Artificial Neural Networks by achieving correlation coefficient (R) value of 0.851 compared to 0.802 respectively. Also, the results showed that regressions of both models achieved a good value of R and lower error values. The main finding from this study is that the Long Short Term Memory to predict the stream flow is little better than the Artificial Neural Networks. 2023-05-03T16:59:14Z 2023-05-03T16:59:14Z 2020-02 https://irepository.uniten.edu.my/handle/123456789/21467 application/pdf
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Stream Flow
Forecast
Artificial Neural Networks (ANN)
Long Short Term Memory (LSTM)
spellingShingle Stream Flow
Forecast
Artificial Neural Networks (ANN)
Long Short Term Memory (LSTM)
Alkatheri Ali Karama Gumaan
Recurrent Neural Network (RNN) For Stream Flow Forecasting
description FYP Sem 2 2019/2020
format
author Alkatheri Ali Karama Gumaan
author_facet Alkatheri Ali Karama Gumaan
author_sort Alkatheri Ali Karama Gumaan
title Recurrent Neural Network (RNN) For Stream Flow Forecasting
title_short Recurrent Neural Network (RNN) For Stream Flow Forecasting
title_full Recurrent Neural Network (RNN) For Stream Flow Forecasting
title_fullStr Recurrent Neural Network (RNN) For Stream Flow Forecasting
title_full_unstemmed Recurrent Neural Network (RNN) For Stream Flow Forecasting
title_sort recurrent neural network (rnn) for stream flow forecasting
publishDate 2023
_version_ 1806425750047293440
score 13.214268

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