In recent years significant breakthroughs in exploring big data, recognition of complex
patterns, and predicting intricate variables have been made. One efficient way of analyzing …

Traditional statistical, physical, and correlation models for chaotic time series prediction
have problems, such as low forecasting accuracy, computational time, and difficulty …

The occurrence of disasters has the potential to impede the progress of sustainable urban
development. For instance, it has the potential to result in significant human casualties and …

Flood nowcasting refers to near-future prediction of flood status as an extreme weather
event unfolds to enhance situational awareness. The objective of this study was to adopt …

Prediction models of heavy rain damage using machine learning based on big data were
developed for the Seoul Capital Area in the Republic of Korea. We used data on the …

The rise in the number and intensity of natural disasters is a serious problem that affects the
whole world. The consequences of these disasters are significantly worse when they occur …

Flood risk management usually hinges on accurate water level identification in urban
streams such as rivers or creeks. Although research has emphasised the applicability of …

The global community is continuously working to minimize the impact of disasters through
various actions, including earth surveying. For example, flood-prone areas must be …

Flood disaster is a major disaster that frequently happens globally, it brings serious impacts
to lives, property, infrastructure and environment. To stop flooding seems to be difficult but to …

Flood is India's most prevalent natural calamity, devastatingly affecting human lives,
infrastructure, and agriculture. Predicting floods can help to mitigate the potential damage …