E-ISSN 3041-4822
 
2024, Vol: 1, Issue: 3
1 / 3Current Issue Online FirstArchiveAims and ScopeAbstracting & IndexingMost Accessed ArticlesMost Downloaded ArticlesMost Cited Articles

Original Article
Online Published: 14 Nov 2024
 


Artificial Neural Network and Ensemble Models for Flood Prediction in North-Central Region of Nigeria

Sikiru Abdulganiyu Siyanbola, Aisha Olabisi Sowemimo, Zaid Habibu, Timothy Ebuka Eberechukwu.


Abstract
Aim of the study: This research investigates the performance of Artificial Neural Network (ANN) and Ensemble models in predicting flood occurrence in the north-central states of Nigeria.
Methods: Meteorological data from the NASA POWER website and flood occurrence data from the Centre for Research on the Epidemiology of Disasters websites were collected. The collected data spanned from 1990 to 2022 for Benue, FCT-Abuja, Kogi, Kwara, Nassarawa, Niger, and Plateau states. The collected data are the input parameters in training the machine learning models: Artificial Neural Networks (ANN), Adaptive Boosting (AdaBoost), Stochastic Gradient Boosting (GBM), Extreme Gradient Boosting (XGBoost), and Random Forest (RF) models, for predicting flood occurrence in the region. The metrics used in evaluating the performance of the models were accuracy score, mean absolute error (MAE), and root mean squared error (RMSE).
Results: The five (5) models achieved high accuracy, with the GBM model demonstrating the best performance by achieving an accuracy of 87.14%, MAE of 0.13, and RMSE of 0.36. The findings also showed that flooding occurs when precipitation is above 500mm. Sensitivity analysis shows that precipitation and minimum temperature are the most significant parameters influencing the model predictions.
Conclusion: ANN and Ensemble models are efficient machine learning techniques for predicting flood occurrence in north-central Nigeria. The GBM model can yield reliable flood predictions for the region.

Key words: Flood prediction, Artificial Neural Network, Ensemble Model, XGBoost, Stochastic Gradient Boosting model, Random Forest, AdaBoost, Machine Learning, Deep Learning


 
ARTICLE TOOLS
Abstract
PDF Fulltext
How to cite this articleHow to cite this article
Citation Tools
Related Records
 Articles by Sikiru Abdulganiyu Siyanbola
Articles by Aisha Olabisi Sowemimo
Articles by Zaid Habibu
Articles by Timothy Ebuka Eberechukwu
on Google
on Google Scholar


How to Cite this Article
Pubmed Style

SAS, Sowemimo AO, Habibu Z, Eberechukwu TE. Artificial Neural Network and Ensemble Models for Flood Prediction in North-Central Region of Nigeria. J Eng Res Rev. 2024; 1(3): 80-87. doi:10.5455/JERR.20240903020517

Web Style

SAS, Sowemimo AO, Habibu Z, Eberechukwu TE. Artificial Neural Network and Ensemble Models for Flood Prediction in North-Central Region of Nigeria. https://www.wisdomgale.com/jerr/?mno=218605 [Access: November 21, 2024]. doi:10.5455/JERR.20240903020517

AMA (American Medical Association) Style

SAS, Sowemimo AO, Habibu Z, Eberechukwu TE. Artificial Neural Network and Ensemble Models for Flood Prediction in North-Central Region of Nigeria. J Eng Res Rev. 2024; 1(3): 80-87. doi:10.5455/JERR.20240903020517


Vancouver/ICMJE Style

SAS, Sowemimo AO, Habibu Z, Eberechukwu TE. Artificial Neural Network and Ensemble Models for Flood Prediction in North-Central Region of Nigeria. J Eng Res Rev. (2024), [cited November 21, 2024]; 1(3): 80-87. doi:10.5455/JERR.20240903020517


Harvard Style

, S. A. S., Sowemimo, . A. O., Habibu, . Z. & Eberechukwu, . T. E. (2024) Artificial Neural Network and Ensemble Models for Flood Prediction in North-Central Region of Nigeria. J Eng Res Rev, 1 (3), 80-87. doi:10.5455/JERR.20240903020517


Turabian Style

, Sikiru Abdulganiyu Siyanbola, Aisha Olabisi Sowemimo, Zaid Habibu, and Timothy Ebuka Eberechukwu. 2024. Artificial Neural Network and Ensemble Models for Flood Prediction in North-Central Region of Nigeria. Journal of Engineering Research and Reviews, 1 (3), 80-87. doi:10.5455/JERR.20240903020517


Chicago Style

, Sikiru Abdulganiyu Siyanbola, Aisha Olabisi Sowemimo, Zaid Habibu, and Timothy Ebuka Eberechukwu. "Artificial Neural Network and Ensemble Models for Flood Prediction in North-Central Region of Nigeria." Journal of Engineering Research and Reviews 1 (2024), 80-87. doi:10.5455/JERR.20240903020517


MLA (The Modern Language Association) Style

, Sikiru Abdulganiyu Siyanbola, Aisha Olabisi Sowemimo, Zaid Habibu, and Timothy Ebuka Eberechukwu. "Artificial Neural Network and Ensemble Models for Flood Prediction in North-Central Region of Nigeria." Journal of Engineering Research and Reviews 1.3 (2024), 80-87. Print. doi:10.5455/JERR.20240903020517


APA (American Psychological Association) Style

, S. A. S., Sowemimo, . A. O., Habibu, . Z. & Eberechukwu, . T. E. (2024) Artificial Neural Network and Ensemble Models for Flood Prediction in North-Central Region of Nigeria. Journal of Engineering Research and Reviews, 1 (3), 80-87. doi:10.5455/JERR.20240903020517


Author LoginReviewer LoginAbout PublisherOpen Access PolicyEditorial PoliciesEditorial Review PolicyPeer Review PolicyEditorial & Peer Review ProcessPublication Ethics and Publication Malpractice StatementConflict of Interest PolicyPlagiarism PolicyProtection of Research Participants (Statement On Human And Animal Rights)Privacy PolicyCorrections, Retractions & Expressions of ConcernSelf-Archiving PoliciesDigital Archiving & Preservation PoliciesTerms of UseLicense InformationCopyright Information

About Journal of Engineering Research and Reviews

Journal of Engineering Research and Reviews is a broad scope, hybrid, international peer reviewed journal publishing articles in all fundamental, applied, ... Read more.



For best results, please use Internet Explorer or Google Chrome.

Contact Information

Your comments are very important to us

We welcome your ideas, suggestions, comments, or questions. To reach Editorial Board please use one of the methods provided below.
 

Emails:

info@wisdomgale.com
editorinchief@ejmanager.com

Office Address:
WisdomGale Publishing
14 Rue de Grand-Bigard,
1082 Brussels
Belgium
 
We will respond within 48 to 72 hours.
 
Change of address or personal information? Please visit your account at www.ejmanager.com to update your information.