Big data analytics for relative humidity time series forecasting based on the LSTM network and ELM

Big data analytics for relative humidity time series forecasting based on the LSTM network and ELM

Accurate and reliable relative humidity forecasting is important when evaluating the impacts of climate change on humans and ecosystems. However, the complex interactions among geophysical parameters are challenging and may result in inaccurate weather forecasting. This study combines long short-ter...

Full description

Bibliographic Details
Main Authors: Kurnianingsih Kurnianingsih, Anindya Wirasatriya, Lutfan Lazuardi, Adi Wibowo, I Ketut Agung Enriko, Wei Hong Chin, Naoyuki Kubota
Format: Article
Language:English
Published: Universitas Ahmad Dahlan 2023-11-01
Series:IJAIN (International Journal of Advances in Intelligent Informatics)
Subjects:
big data analytics
relative humidity
time series forecasting
lstm
elm
Online Access:http://ijain.org/index.php/IJAIN/article/view/905

Similar Items

Similar Items