Flood forecasting is an important non-structural approach for flood mitigation. The flood
stage is chosen as the variable to be forecasted because it is practically useful in flood …

An accurate and timely prediction of river flow flooding can provide time for the authorities to
take pertinent flood protection measures such as evacuation. Various data-derived models …

In this study, five different artificial intelligence methods, including Artificial Neural Networks
based on Particle Swarm Optimization (PSO-ANN), Support Vector Regression (SVR), Multi …

This study is to perform real-time probabilistic flood stage forecasting. The proposed method
consists of a deterministic stage forecast derived from the support vector regression, and a …

An accurate and real-time flood forecast is a crucial nonstructural step to flood mitigation. A
support vector machine (SVM) is based on the principle of structural risk minimization and …

Though large amounts of work with artificial intelligence are used in typhoon rainfall
forecasting, the predictive skills of existing models are unsatisfactory. To address this …

Understanding the impact of input variables on black‐box machine learning and deep
learning models is necessary. Therefore, this study proposed SHapley Additive …

The support vector machine, a novel artificial intelligence-based approach developed from
statistical learning theory, is used in this work to develop a real-time stage forecasting …

Flooding is a destructive phenomenon that can risk human life, damage homes and have
huge economic impacts. To plan and implement effective mitigation strategies, it is …

The Runoff forecasting is an important factor in river basin management. In this paper, we
use fuzzy support vector machine regression (FSVMR) to predict the Runoff of Yom River at …