Current - Issue

1. M. Krichen, M. S. Abdalzaher, M. Elwekeil, and M. M. Fouda, “Managing natural disasters: An analysis of technological advancements,
opportunities, and challenges,” Internet of Things and Cyber-Physical Systems, vol. 4, pp. 99–109, Sept. 2023, doi:
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2. F. Mushtaq, A. P. Krishna, M. K. Ponnambalam, and T. V. Joydas, “Hazards and Extreme Climate Events in the Arabian Peninsula: Patterns,
Drivers and Resilience Pathways,” Climate Change in the Arabian Peninsula, pp. 95–127, 2026, doi: 10.1007/978-3-032-02481-7_5.
3. D. S. Mileti and J. H. Sorensen, “Communication of emergency public warnings: A social science perspective and state-of-the-art
assessment,” Aug. 1990, doi: 10.2172/6137387.
4. V. Kumar Karne, S.S.M. Dandyala, P.R. Kothamali and N. Srinivas, “Enhancing Environmental Monitoring and Disaster Prediction with
AI”. International Journal of Advanced Engineering Technologies and Innovations, 1(3),2021.
5. T. Tiggeloven, S. Pfeiffer, A. Matanó, M. van den Homberg, L. Thalheimer, M. Reichstein, and S. Torresan, “ The Role of Artificial
Intelligence for Early Warning Systems: Status, Applicability, Guardrails and Ways Forward”. iScience, p.113689, 2025, doi:
https://doi.org/10.1016/j.isci.2025.113689.
6. M.M. Islam, M. Hasan, M.S. Mia, A.A. Masud, and Abu , “ Early Warning Systems in Climate Risk Management: Roles and
Implementations in Eradicating Barriers and Overcoming Challenges”. Natural Hazards Research, 5(3), pp.523–538,2025,
doi:https://doi.org/10.1016/j.nhres.2025.01.007.
7. J. P. Newman, H. R. Maier, G. A. Riddell, A. C. Zecchin, J. E. Daniell, A. M. Schaefer, H. van Delden, B. Khazai, M. J. O'Flaherty, and C.
P. Newland, "Review of literature on decision support systems for natural hazard risk reduction: Current status and future research
directions," Environmental Modelling & Software, vol. 96, pp. 378–409, 2017, doi: 10.1016/j.envsoft.2017.06.042.
8. M. Fazeli, A. Hosseini, H. Moghaddasi, F. Asadi, and H. Haghighi, "Designing an Architectural Model of Crisis Management Information
System for Natural Disasters in Iran," 2020, doi: 10.22037/aab.v11i4.32310.
9. S. Lee, G. Landucci, G. Reniers, and N. Paltrinieri, "Validation of Dynamic Risk Analysis Supporting Integrated Operations Across
Systems," Sustainability, vol. 11, no. 23, Art. no. 6745, 2019, doi: 10.3390/su11236745.
10. A. S. Albahri, Y. L. Khaleel, M. A. Habeeb, R. D. Ismael, Q. A. Hameed, M. Deveci, R. Z. Homod, O. S. Albahri, A. H. Alamoodi, and L.
Alzubaidi, "A systematic review of trustworthy artificial intelligence applications in natural disasters," Computers & Electrical Engineering,
vol. 118, Art. no. 109409, 2024, doi: 10.1016/j.compeleceng.2024.109409.
11. A. E. Collins, "Advancing the Disaster and Development Paradigm," International Journal of Disaster Risk Science, vol. 9, no. 4, pp. 486–
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13. M. Wahlström, "Sendai Framework for Disaster Risk Reduction 2015–2030," in Proceedings of the Third UN World Conference on Disaster
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14. V. Jayawardene, T. J. Huggins, R. Prasanna, and B. Fakhruddin, "The role of data and information quality during disaster response decision-
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15. P. Chavula, F. Kayusi, G. Lungu, and A. Uwimbabazi, "The Current Landscape of Early Warning Systems and Traditional Approaches to
Disaster Detection," LatIA, vol. 3, Art. no. 77, 2025, doi: 10.62486/latia202577.
16. D. Faulkner, T. Kjeldsen, J. Packman, and L. Stewart, Estimating Flood Peaks and Hydrographs for Small Catchments: Phase 1. Bristol,
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17. A. A. A. Dallaf, "Edge Computing in IoT Networks: Enhancing Efficiency, Reducing Latency, and Improving Scalability," International
Journal of Advanced Network Monitoring and Computing, vol. 10, no. 1, Art. no. 2025, 2025, doi: 10.2478/ijanmc-2025-0009.
18. M. Gangi, O. M. Belcore, and A. Polimeni, "An Overview on Decision Support Systems for Risk Management in Emergency Conditions:
Present, Past and Future Trends," International Journal of Transport Development and Integration, vol. 7, no. 1, pp. 45–53, 2023, doi:
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19. H. Taherdoost and M. Madanchian, "Multi-Criteria Decision Making (MCDM) Methods and Concepts," Encyclopedia, vol. 3, no. 1, pp.
77–87, 2023, doi: 10.3390/encyclopedia3010006.
20. P. Ziemba, "NEAT F-PROMETHEE—A new fuzzy multiple criteria decision-making method based on the adjustment of mapping
trapezoidal fuzzy numbers," Expert Systems with Applications, vol. 110, pp. 363–380, 2018, doi: 10.1016/j.eswa.2018.06.008.21. S. Kodors, I. Apeinans, I. Zarembo, and J. Lonska, "RecGen: No-Coding Shell of Rule-Based Expert System with Digital Twin and
Capability-Driven Approach Elements for Building Recommendation Systems," Applied Sciences, vol. 15, no. 19, Art. no. 10482, 2025,
doi: 10.3390/app151910482.
22. E. K. Zavadskas, K. Govindan, J. Antucheviciene, and Z. Turskis, "Hybrid Multiple Criteria Decision-Making Methods: A Review of
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23. S. M. Bonnet, A. Evsukoff, and C. A. M. Rodriguez, "Precipitation Nowcasting with Weather Radar Images and Deep Learning in São
Paulo, Brazil," Atmosphere, vol. 11, no. 11, Art. no. 1157, 2020, doi: 10.3390/atmos11111157.
24. A. S. Ahmar and A. Mokhtar, "Evaluating ARIMA Models for Short-Term Rainfall Forecasting in Polewali Mandar Regency," Journal of
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25. M. Imani, A. Beikmohammadi, and H. R. Arabnia, "Comprehensive Analysis of Random Forest and XGBoost Performance with SMOTE,
ADASYN, and GNUS Under Varying Imbalance Levels," Technologies, vol. 13, no. 3, Art. no. 88, 2025, doi:
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26. X. Wu, Z. Zhang, W. Zhang, B. An, Z. Li, R. Li, and Q. Chen, "Large-Scale Flood Detection and Mapping in the Yangtze River Basin
(2016–2021) Using Convolutional Neural Networks with Sentinel-1 SAR Images," Remote Sensing, vol. 17, no. 16, Art. no. 2909, 2025,
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27. Q. Han, B. Huang, and Y. Li, "SAR-Conditioned Consistency Model for Effective Cloud Removal in Remote Sensing Images," Remote
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28. O. A. Hassen, H. L. Majeed, A. R. Khraibet, and M. Iraq, "Anomaly Detection in Satellite Imagery Using Deep Autoencoders," Fusion
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29. R. Okonkwo, A. Folorunso, F. Ogundipe, and C. Y. Tettey, "Explainable Artificial Intelligence (AI) Through Human-AI Collaborative
Frameworks: Quantifying Trust and Interpretability in High-Stakes Decisions," Computer Science & IT Research Journal, vol. 6, no. 5, pp.
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30. C. D. Salvo, F. Pennica, G. Ciotoli, and G. P. Cavinato, "A GIS-Based Procedure for Preliminary Mapping of Pluvial Flood Risk at
Metropolitan Scale," Environmental Modelling & Software, vol. 107, pp. 64–84, 2018, doi: 10.1016/j.envsoft.2018.05.020.
31. K. Turesson, A. Pettersson, M. Hervé, J. Gustavsson, J. Haas, J. Koivisto, K. Karagiorgos, and L. Nyberg, "The Human Dimension of
Vulnerability: A Scoping Review of the Nordic Literature on Factors for Social Vulnerability to Climate Risks," International Journal of
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32. X. Zheng, K. Wang, and M. Liu, "A Bayesian Network and DEMATEL-ISM Approach for Smart Community Flood Risk Assessment,"
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