Predicting Gross Domestic Product (GDP) using a PC-LSTM-RNN model in urban profiling areas

Predicting Gross Domestic Product (GDP) using a PC-LSTM-RNN model in urban profiling areas

Abstract Gross Domestic Product (GDP) is significant for measuring the strength of national and global economies in urban profiling areas. GDP is significant because it provides information on the size and performance of an economy. The real GDP growth rate is frequently used to indicate the economy...

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Bibliographic Details
Main Authors: Mahmoud Y. Shams, Zahraa Tarek, El-Sayed M. El-kenawy, Marwa M. Eid, Ahmed M. Elshewey
Format: Article
Language:English
Published: Springer 2024-01-01
Series:Computational Urban Science
Subjects:
Smart cities
Gross domestic product
Prediction
Pearson correlation
LSTM
RNN
Online Access:https://doi.org/10.1007/s43762-024-00116-2

Internet

https://doi.org/10.1007/s43762-024-00116-2

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