The effect of standard transformation of data to the data-driven hydrological model
文献类型：EI期刊论文
| 作者 | Ge Yong-Gang ; Xiong Li-Hua ; Chen Xiang-Dong ; Wu Jian |
| 发表日期 | 2009 |
| 关键词 | Flood control Fuzzy inference Hydraulic models Rain Runoff Standards Weather forecasting |
| 英文摘要 | The data-driven hydrological model is established based on the historical input and output data, whereas there often exists a data-scale difference between the input and output variables, which may influence the modeling or forecasting accuracy of the established model. A standard transformation of the data before establishing the model may have an actual effect to deal with this problem. In this paper, a comparative study is done between the performance of two kinds of models, named rainfall-runoff modeling model based on the adaptive neuro-fuzzy inference system (ANFIS-RRM) and real-time flood forecasting model based on adaptive neuro-fuzzy inference system (ANFIS-RFFM), which both are separately established based on the raw data and the standard transformed data. It is found that the standard transformation of the data can improve the model forecasting accuracy greatly. |
| 出处 | Sichuan Daxue Xuebao (Gongcheng Kexue Ban)/Journal of Sichuan University (Engineering Science Edition)
 |
| 卷 | 41期:SUPPL. 2页:66-69 |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/24901]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Ge Yong-Gang,Xiong Li-Hua,Chen Xiang-Dong,et al. The effect of standard transformation of data to the data-driven hydrological model. 2009. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。