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Deterministic Analysis and Uncertainty Analysis of Ensemble Forecasting Model Based on Variational Mode Decomposition for Estimation of Monthly Groundwater Level 期刊论文
WATER, 2021, 卷号: 13, 期号: 2
作者:  Wu, Min;  Feng, Qi;  Wen, Xiaohu;  Yin, Zhenliang;  Yang, Linshan;  Sheng, Danrui
收藏  |  浏览/下载：31/0  |  提交时间：2021/12/07
Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data 期刊论文
REMOTE SENSING, 2021, 卷号: 13, 期号: 4
作者:  Ahmed, A. A. Masrur;  Deo, Ravinesh C.;  Raj, Nawin;  Ghahramani, Afshin;  Feng, Qi;  Yin, Zhenliang;  Yang, Linshan
收藏  |  浏览/下载：28/0  |  提交时间：2021/12/07
Hybrid deep learning method for a week-ahead evapotranspiration forecasting 期刊论文
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2021
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：23/0  |  提交时间：2021/12/07
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：36/0  |  提交时间：2021/12/07
LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios 期刊论文
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2021, 卷号: 35, 期号: 9
作者:  Ahmed, A. A. Masrur;  Deo, Ravinesh C.;  Ghahramani, Afshin;  Raj, Nawin;  Feng, Qi;  Yin, Zhenliang;  Yang, Linshan
收藏  |  浏览/下载：30/0  |  提交时间：2021/12/07
Spatio-temporal variation of reference evapotranspiration in northwest China based on CORDEX-EA 期刊论文
ATMOSPHERIC RESEARCH, 2020, 卷号: 238
作者:  Yang, Linshan;  Feng, Qi;  Adamowski, Jan F.;  Yin, Zhenliang;  Wen, Xiaohu;  Wu, Min;  Jia, Bing;  Hao, Qiang
收藏  |  浏览/下载：23/0  |  提交时间：2021/12/07
Random forest predictive model development with uncertainty analysis capability for the estimation of evapotranspiration in an arid oasis region 期刊论文
HYDROLOGY RESEARCH, 2020, 卷号: 51, 期号: 4
作者:  Wu, Min;  Feng, Qi;  Wen, Xiaohu;  Deo, Ravinesh C.;  Yin, Zhenliang;  Yang, Linshan;  Sheng, Danrui
收藏  |  浏览/下载：20/0  |  提交时间：2021/12/07
Two-phase extreme learning machines integrated with the complete ensemble empirical mode decomposition with adaptive noise algorithm for multi-scale runoff prediction problems 期刊论文
JOURNAL OF HYDROLOGY, 2019, 卷号: 570
作者:  Wen, Xiaohu;  Feng, Qi;  Deo, Ravinesh C.;  Wu, Min;  Yin, Zhenliang;  Yang, Linshan;  Singh, Vijay P.
收藏  |  浏览/下载：33/0  |  提交时间：2019/11/08
Expert system  Runoff  Integrated model  Complete ensemble empirical mode decomposition adaptive noise (CEEMDAN)  Variational mode decomposition (VMD)  Extreme learning machine (ELM)  
Integrating genetic algorithm and support vector machine for modeling daily reference evapotranspiration in a semi-arid mountain area 期刊论文
Hydrology Research, 2017, 卷号: v 48, 期号: n 5, 页码: p 1177-1191
作者:  Yin, Zhenliang;  Wen, Xiaohu;  Feng, Qi;  He, Zhibin;  Zou, Songbing;  Yang, Linshan
收藏  |  浏览/下载：16/0  |  提交时间：2021/12/07
Future Projection with an Extreme-Learning Machine and Support Vector Regression of Reference Evapotranspiration in a Mountainous Inland Watershed in North-West China 期刊论文
WATER, 2017, 卷号: 9, 期号: 11
作者:  Yin, Zhenliang;  Feng, Qi;  Yang, Linshan;  Deo, Ravinesh C.;  Wen, Xiaohu;  Si, Jianhua;  Xiao, Shengchun
收藏  |  浏览/下载：44/0  |  提交时间：2019/11/08
reference evapotranspiration (ET0)  extreme-learning machine  support vector regression  ET0 projection  climate change