Abstract
Probabilistic typhoon rainfall forecasting using a modified fuzzy inference model
Highlights
Machine learning methods are extensively applied to hydrologic forecasting in hydroinformatics
The architecture of the probabilistic typhoon rainfall forecasting model can be formulated in terms of a fuzzy rule as follows
This study proposed a probabilistic typhoon rainfall forecasting method using a modified fuzzy inference model
Summary
Machine learning methods are extensively applied to hydrologic forecasting in hydroinformatics. Various machine learning methods have been applied to real-time hydrologic forecasting to forecast variables related to rainfall and flood. Various methods based on fuzzy set theory have been applied to rainfall forecasting (Yu et al 2004, 2005; Asklany et al 2011) and flood forecasting (Yu and Chen 2005; Chen et al 2013a, 2019). Grey system theory has been adopted to develop forecasting models that forecast rainfall (Yu et al 2000), runoff (Yu et al 2001), and flood stages (Chen 2015a). Popular in recent hydroinformatics research, have been
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