[HTML][HTML] An integrated risk-based early warning system to increase community resilience against disaster

A Haque, M Akter, MM Hussain, MR Rahman… - Progress in Disaster …, 2024 - Elsevier
The need to integrate Early Warning System (EWS) with Disaster Risk Reduction (DRR) has
long been recognized in several global forums. In the year 2006, the United Nations …

A Data‐Driven Method and Hybrid Deep Learning Model for Flood Risk Prediction

C Ni, PS Fam, MF Marsani - International Journal of Intelligent …, 2024 - Wiley Online Library
Flood disasters occur worldwide, and flood risk prediction is conducive to protecting human
life and property safety. Influenced by topographic changes and rainfall, the water level …

Time-series-analysis-based detection of critical transitions in real-world non-autonomous systems

K Lehnertz - Chaos: An Interdisciplinary Journal of Nonlinear …, 2024 - pubs.aip.org
Real-world non-autonomous systems are open, out-of-equilibrium systems that evolve in
and are driven by temporally varying environments. Such systems can show multiple …

Identifying extreme events in the stock market: A topological data analysis

A Rai, B Nath Sharma, S Rabindrajit Luwang… - … Journal of Nonlinear …, 2024 - pubs.aip.org
This paper employs Topological Data Analysis (TDA) to detect extreme events (EEs) in the
stock market at a continental level. Previous approaches, which analyzed stock indices …

Critical slowing down theory provides early warning signals for sandstone failure

Y Tang, X Zhu, C He, J Hu, J Fan - Frontiers in Earth Science, 2022 - frontiersin.org
The critical point of rock mass transition from stable to unstable states is significant for the
prevention and control of rock engineering hazards. This study explored the precursor …

Topological clustering in investigating spatial patterns of particulate matter between air quality monitoring stations in malaysia

NFS Zulkepli, VN Madukpe, MSM Noorani… - Air Quality, Atmosphere …, 2024 - Springer
Air pollution is a persistent issue that arises worldwide. Mitigating this issue poses a
significant challenge due to endless industrialization activities, rising construction works and …

Hybridization of hierarchical clustering with persistent homology in assessing haze episodes between air quality monitoring stations

NFS Zulkepli, MSM Noorani, FA Razak, M Ismail… - Journal of environmental …, 2022 - Elsevier
Haze has been a major issue afflicting Southeast Asian countries, including Malaysia, for the
past few decades. Hierarchical agglomerative cluster analysis (HACA) is commonly used to …

[PDF][PDF] Application of topological data analysis to flood disaster management in Nigeria

FO Ohanuba, MT Ismail, MKM Ali - Environmental Engineering Research, 2023 - eeer.org
The importance of this research to the literature lies in the ability to develop a hybrid method
of Topological Data Analysis and Unsupervised Machine Learning (TDA-uML) for flood …

[HTML][HTML] Topological data analysis via unsupervised machine learning for recognizing atmospheric river patterns on flood detection

FO Ohanuba, MT Ismail, MKM Ali - Scientific African, 2021 - Elsevier
Topological data analysis (TDA) has recently been a very reliable research area in Statistics
for extracting shape from data. Flooding annually destroys properties, buildings, farmland …

Automated earthwork detection using topological persistence

DA Lapides, G Grindstaff… - Water Resources …, 2024 - Wiley Online Library
For thousands of years, humans have altered the movement of water through construction of
earthworks. These earthworks remain in landscapes, where they continue to alter hydrology …