Advanced stacked integration method for forecasting long-term drought severity: CNN with machine learning models

Advanced stacked integration method for forecasting long-term drought severity: CNN with machine learning models

Study region: Eight governorates in upper Egypt namely Aswan, Asyut, Beni-Suef, Fayoum, Luxor, Minya, Qena and Sohag. Study focus: This study aims to develop novel hybrid machine learning (ML) models for forecasting the drought phenomena based on limited inputs for the eight Egyptian govern-orates,...

Full description

Bibliographic Details
Main Authors: Ahmed Elbeltagi, Aman Srivastava, Muhsan Ehsan, Gitika Sharma, Jiawen Yu, Leena Khadke, Vinay Kumar Gautam, Ahmed Awad, Deng Jinsong
Format: Article
Language:English
Published: Elsevier 2024-06-01
Series:Journal of Hydrology: Regional Studies
Subjects:
PDSI models
Long short-term memory
Convolution Neural Networks
Extreme gradient boosting
Support vector machine
Upper Egypt
Online Access:http://www.sciencedirect.com/science/article/pii/S2214581824001071

Internet

http://www.sciencedirect.com/science/article/pii/S2214581824001071

Similar Items