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AN Approach for Data Analysis and Forecasting with Neuro Fuzzy Systems-Demonstrated on Flood Events at River Mosel

机译:用神经模糊系统进行数据分析和预测的一种方法-以Mosel河洪水事件为例

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摘要

The development and usage of soft computing systems for forecasting fo 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 posibilities 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 testd and satisfying results are shown with practical data.
机译:介绍了在Mosel河发生洪水事件时预测水位进度的软计算系统的开发和使用。解释了实际情况及其要求,并讨论了两种不同的系统方法:a)用于监督学习时间序列数据的功能行为及其近似的神经网络,以及b)具有系统行为建模能力的模糊系统利用专家信息并进行系统优化。描述了这两种概念的优缺点,并着重于模糊系统的结构发展。两种系统都经过了测试,并通过实际数据显示了令人满意的结果。

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