An approach for data analysis and forecasting with neuro fuzzy systems — Demonstrated on flood events at river Mosel

Abstract

The development and usage of soft computing systems for forecasting of water level progress in case of flood events at river Mosel are presented. The practical situation and its requirements are explained and two different system approaches are discussed: a) a neural network for supervised learning of the functional behavior of time series data and its approximation, and b) a fuzzy system for modeling of the system behavior with possibilities to exploit expert information and for systematic optimization. Advantages and disadvantages of both concepts are described and emphasis is laid on the structural development of the fuzzy system. Both systems have been tested and satisfying results are shown with practical data.