CCPortal

浏览/检索结果: 共5条,第1-5条 帮助

限定条件            
已选(0)清除 条数/页:   排序方式:
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:32/0  |  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:29/0  |  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:38/0  |  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:31/0  |  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:43/0  |  提交时间:2019/11/08
River flow forecasting  Support vector regression  Multivariate adaptive regression spline  M5Tree model  Data-driven model