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Deep Learning-Based Predictive Framework for Groundwater Level Forecast in Arid Irrigated Areas 期刊论文
WATER, 2021, 卷号: 13, 期号: 18
作者:  Liu, Wei;  Yu, Haijiao;  Yang, Linshan;  Yin, Zhenliang;  Zhu, Meng;  Wen, Xiaohu
收藏  |  浏览/下载：15/0  |  提交时间：2022/04/28
EMPIRICAL MODE DECOMPOSITION  WAVELET ANALYSIS  QUANTILE REGRESSION  ALGORITHM  DEPTH  QUANTIFICATION  UNCERTAINTY  RECHARGE  MACHINES  DESIGN  
Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity 期刊论文
JOURNAL OF HYDROLOGY, 2021, 卷号: 599
作者:  Ahmed, A. A. Masrur;  Deo, Ravinesh C.;  Feng, Qi;  Ghahramani, Afshin;  Raj, Nawin;  Yin, Zhenliang;  Yang, Linshan
收藏  |  浏览/下载：38/0  |  提交时间：2021/12/07
Design and evaluation of SVR, MARS and M5Tree models for 1, 2 and 3-day lead time forecasting of river flow data in a semiarid mountainous catchment 期刊论文
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2018, 卷号: 32, 期号: 9
作者:  Yin, Zhenliang;  Feng, Qi;  Wen, Xiaohu;  Deo, Ravinesh C.;  Yang, Linshan;  Si, Jianhua;  He, Zhibin
收藏  |  浏览/下载：45/0  |  提交时间：2019/11/08
River flow forecasting  Support vector regression  Multivariate adaptive regression spline  M5Tree model  Data-driven model