Application of SOM-RBFN model for groundwater level forecasting

• Main Authors: Yan-Gu Pan, 潘衍谷
• Other Authors: Ching-Tien Chen Ph. D.
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/22512287887310711478

碩士 === 國立嘉義大學 === 土木與水資源工程學系研究所 === 95 === Recently, the correlation influence of global warming and climatic changes causes the significant changing of hydrology environment. The warming current of Taiwan is the same as global’s, and intensifies the tendency of north waterlogging and south drought. Thus, it demonstrates the importance of water resource management. However, it is difficult to search new surface water resource in the short term in Taiwan. Therefore, the groundwater use plays a decisive role under using the premise of limited water resource. In this paper, a groundwater level forecasting model is proposed by combing the theory of self-organizing map(SOM) and radial basis function network(RBFN). It is examined by simulated six groundwater stations’s data in Douliou city, Yunlin county. Traditionally, the number of hidden units and the positioning of the radial basis centers are crucial problems for establishing RBFN. The result shows that proposed model can decide the number of RBFN’s hidden units with using the two-dimensional feature map which is constructed by SOM, and then it can determine the positioning of the radial basis centers easily. Finally, the proposed model is applied to actual groundwater head data. It is found that the proposed model which with mult-stations’ data can forecast more precisely than single, but it has the direct ratio by no means percison. For groundwater level forecasting, the proposed model which with mult-stations’ data is recommended as an alternative to the other method, because it has a simple structure and can produce more reasonable forecasts.