Developing rainfall-runoff distributed model by Decision Group Artificial Neural Network in Wu Chi River
碩士 === 逢甲大學 === 水利工程與資源保育研究所 === 100 === The rainfall-runoff is a complicated and non-linear time-variant system. The rainfall-runoff model is usually a catchment lumped system. This research used the artificial neural network combined with a predictions distribution model of simulated rainfall-runo...
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| Format: | Others |
| Language: | zh-TW |
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2012
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| Online Access: | http://ndltd.ncl.edu.tw/handle/24728487518316958618 |
| Summary: | 碩士 === 逢甲大學 === 水利工程與資源保育研究所 === 100 === The rainfall-runoff is a complicated and non-linear time-variant system. The rainfall-runoff model is usually a catchment lumped system. This research used the artificial neural network combined with a predictions distribution model of simulated rainfall-runoff. Hydrometric station locations we used to describe the catchment. A River system channel network was combined with the artificial neural network to construct a overland flow model and a channel flow model. Each model was then attached to the entire rainfall-runoff catchment.
This paper proposes the practices in the typhoon’s data classification. Numerous models were constructed with the Euclidean norm to determine the best model for simulated rainfall runoff. However, as the hydrologic system is unpredictable, we can’t a deterministic model of simulated rainfall runoff. In this study the deterministic model was combined with fuzzy theory of simulated rainfall runoff. This research forecasted discharge at Wu-Xi watershed. Predictions made form this model provide accurate results. In the future, decision maker will have a reliable model to forecast discharge.
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