Long Qian

发表

Scientific Machine Learning Framework to Understand Flash Graphene Synthesis

J. Tour, Jian Lin, Kianoosh Sattari, 2023, 2303.12638.

Time-delayed machine learning models for estimating groundwater depth in the Hetao Irrigation District, China

W. Zeng, T. Gaiser, Lifeng Wu, 2021 .

Review on Drip Irrigation: Impact on Crop Yield, Quality, and Water Productivity in China

Junliang Fan, Sien Li, Hai-dong Wang, 2023, Water.

A study of the conversion of different evaporation pans in South China based on the extreme learning machine model

Yaokui Cui, Xiaogang Liu, Sien Li, 2021 .

Assessment of Daily of Reference Evapotranspiration Using CLDAS Product in Different Climate Regions of China

H. Bai, Shaofei Wu, Long Qian, 2022, Water.

Comprehensive evaluation of terrestrial evapotranspiration from different models under extreme condition over conterminous United States

Wene Wang, Long Qian, Xingjiao Yu, 2023, Agricultural Water Management.

Assessing and Comparing Reference Evapotranspiration across Different Climatic Regions of China Using Reanalysis Products

Xiaotao Hu, Wene Wang, Long Qian, 2023, Water.

Comparison of CLDAS and Machine Learning Models for Reference Evapotranspiration Estimation under Limited Meteorological Data

Yaokui Cui, Xiaogang Liu, Lifeng Wu, 2022, Sustainability.

High uncertainty of evapotranspiration products under extreme climatic conditions

Long Qian, Yalan Ba, Xingjiao Yu, 2023, Journal of Hydrology.

Improving high uncertainty of evapotranspiration products under extreme climatic conditions based on deep learning and ERA5 reanalysis data

Long Qian, Xingjiao Yu, Yaokui Cui, 2024, Journal of Hydrology.

Assessing and improving the high uncertainty of global gross primary productivity products based on deep learning under extreme climatic conditions.

Youzhen Xiang, Long Qian, Xingjiao Yu, 2024, The Science of the total environment.