Rainfall-based flood prediction by hybrid deep architecture with entropy and statistical feature set

Vanam Yoganand 1
, 
B Sheela Rani 1
, 
Nagamani Kattukota 1
, 
Eppakayala Balakrishna 2
, 
Mohammad Suhail Meer 1
1
 
2
 
Vaagdevi College of Engineering
Publication type: Journal Article
Publication date: 2025-03-09
Taylor & Francis
scimago Q2
wos Q4
SJR: 0.459
CiteScore: 3.9
Impact factor: 1.3
ISSN: 19479832, 19479824
Found 
Found 

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Yoganand V. et al. Rainfall-based flood prediction by hybrid deep architecture with entropy and statistical feature set // International Journal of Image and Data Fusion. 2025. Vol. 16. No. 1.
GOST all authors (up to 50) Copy
Yoganand V., Sheela Rani B., Kattukota N., Balakrishna E., Meer M. S. Rainfall-based flood prediction by hybrid deep architecture with entropy and statistical feature set // International Journal of Image and Data Fusion. 2025. Vol. 16. No. 1.
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RIS Copy
TY - JOUR
DO - 10.1080/19479832.2024.2427212
UR - https://www.tandfonline.com/doi/full/10.1080/19479832.2024.2427212
TI - Rainfall-based flood prediction by hybrid deep architecture with entropy and statistical feature set
T2 - International Journal of Image and Data Fusion
AU - Yoganand, Vanam
AU - Sheela Rani, B
AU - Kattukota, Nagamani
AU - Balakrishna, Eppakayala
AU - Meer, Mohammad Suhail
PY - 2025
DA - 2025/03/09
PB - Taylor & Francis
IS - 1
VL - 16
SN - 1947-9832
SN - 1947-9824
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2025_Yoganand,
author = {Vanam Yoganand and B Sheela Rani and Nagamani Kattukota and Eppakayala Balakrishna and Mohammad Suhail Meer},
title = {Rainfall-based flood prediction by hybrid deep architecture with entropy and statistical feature set},
journal = {International Journal of Image and Data Fusion},
year = {2025},
volume = {16},
publisher = {Taylor & Francis},
month = {mar},
url = {https://www.tandfonline.com/doi/full/10.1080/19479832.2024.2427212},
number = {1},
doi = {10.1080/19479832.2024.2427212}
}