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Projected spatial patterns in precipitation and air temperature for China's northwest region derived from high-resolution regional climate models 期刊论文
International Journal of Climatology, 2020, 卷号: v 40, 期号: n 8, 页码: p 3922-3941
作者:  Yin, Zhenliang;  Feng, Qi;  Yang, Linshan;  Deo, Ravinesh C.;  Adamowski, Jan F.;  Wen, Xiaohu;  Jia, Bing;  Si, Jianhua
收藏  |  浏览/下载：26/0  |  提交时间：2021/12/07
Causality of climate, food production and conflict over the last two millennia in the Hexi Corridor, China 期刊论文
Science of the Total Environment, 2020, 卷号: v 713
作者:  Yang, Linshan;  Feng, Qi;  Adamowski, Jan F.;  Deo, Ravinesh C.;  Yin, Zhenliang;  Wen, Xiaohu;  Tang, Xia;  Wu, Min
收藏  |  浏览/下载：0/0  |  提交时间：2021/12/07
Random forest predictive model development w i t h uncertainty analysis capability for the estimation of evapotranspiration in an arid oasis region 期刊论文
Hydrology Research, 2020, 卷号: v 51, 期号: n 4, 页码: p 648-665
作者:  Wu, Min;  Feng, Qi;  Wen, Xiaohu;  Deo, Ravinesh C.;  Yin, Zhenliang;  Yang, Linshan;  Sheng, Danrui
收藏  |  浏览/下载：24/0  |  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: v 570, 页码: p 167-184
作者:  Wen, Xiaohu;  Feng, Qi;  Deo, Ravinesh C.;  Wu, Min;  Yin, Zhenliang;  Yang, Linshan;  Singh, Vijay P
收藏  |  浏览/下载：1/0  |  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：38/0  |  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)  
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: v 32, 期号: n 9, 页码: p 2457-2476
作者:  Yin, Zhenliang;  Feng, Qi;  Wen, Xiaohu;  Deo, Ravinesh C.;  Yang, Linshan;  Si, Jianhua;  He, Zhibin
收藏  |  浏览/下载：30/0  |  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：46/0  |  提交时间：2019/11/08
River flow forecasting  Support vector regression  Multivariate adaptive regression spline  M5Tree model  Data-driven model  
Identifying separate impacts of climate and land use/cover change on hydrological processes in upper stream of Heihe River, Northwest China 期刊论文
Hydrological Processes, 2017, 卷号: v 31, 期号: n 5, 页码: p 1100-1112
作者:  Yang, Linshan;  Feng, Qi;  Yin, Zhenliang;  Wen, Xiaohu;  Si, Jianhua;  Li, Changbin;  Deo, Ravinesh C.
收藏  |  浏览/下载：27/0  |  提交时间：2021/12/07
Identifying separate impacts of climate and land use/cover change on hydrological processes in upper stream of Heihe River, Northwest China 期刊论文
HYDROLOGICAL PROCESSES, 2017, 卷号: 31, 期号: 5
作者:  Yang, Linshan;  Feng, Qi;  Yin, Zhenliang;  Wen, Xiaohu;  Si, Jianhua;  Li, Changbin;  Deo, Ravinesh C.
收藏  |  浏览/下载：33/0  |  提交时间：2019/11/08
climate change  Heihe River Basin  hydrological processes  LUCC  SWAT  
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：51/0  |  提交时间：2019/11/08
reference evapotranspiration (ET0)  extreme-learning machine  support vector regression  ET0 projection  climate change