A Comparative Study of LSTM, GRU, BiLSTM and BiGRU to Predict Dissolved Oxygen-Reference-Cited by-同舟云学术

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A Comparative Study of LSTM, GRU, BiLSTM and BiGRU to Predict Dissolved Oxygen

Published:2023-06-28 Issue: Volume: Page:
ISSN:
Container-title:2023 20th International Joint Conference on Computer Science and Software Engineering (JCSSE)
language:
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Author:

Putpuek Narongsak¹,Putpuek Apiradee¹,Sungthong Apichart²

Affiliation:

1. Rajabhat Rajanagarindra University,Faculty of Science and Technology,Department of Information Technology,Chachoengsao,Thailand

2. Rajabhat Rajanagarindra University,Faculty of Science and Technology,Department of Applied Physics,Chachoengsao,Thailand

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10201904/10201936/10202128.pdf?arnumber=10202128

Reference23 articles.

1. Deep Learning-Based Stock Price Prediction Using LSTM and Bi-Directional LSTM Model

2. Learning temporal representation of transaction amount for fraudulent transaction recognition using CNN, Stacked LSTM, and CNN-LSTM

3. Mutually Informed Correlation Coefficient (MICC) - a New Filter Based Feature Selection Method

4. COVID-19 positive cases prediction based on LSTM algorithm and its variants

5. Short-Term Traffic Forecasting using LSTM-based Deep Learning Models

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Analyzing Machine Learning Techniques for Air Passenger Numbers Forecasting;2024 21st International Joint Conference on Computer Science and Software Engineering (JCSSE);2024-06-19

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