Wenze Li

A machine learning correction for DFT non-covalent interactions based on the S22, S66 and X40 benchmark databases

Hui Li, Hong-Zhi Li, Yinghua Lu, 2016, Journal of Cheminformatics.

Efficient Corrections for DFT Noncovalent Interactions Based on Ensemble Learning Models

Yinghua Lu, Chao Fang, Jingxia Cui, 2019, J. Chem. Inf. Model..

AdaBoost Ensemble Correction Models for TDDFT Calculated Absorption Energies

Ting Gao, Chao Fang, Yinghua Lu, 2019, IEEE Access.

A novel two‐stage interval prediction method based on minimal gated memory network for clustered wind power forecasting

Xiaosheng Peng, Chaoshun Li, Tao Cai, 2020 .

A novel ZigBee based high speed Ad Hoc communication network

Shaosheng Li, Jianxun Zhu, Wenze Li, 2009, 2009 IEEE International Conference on Network Infrastructure and Digital Content.

Short-Term Wind Power Prediction Based on Wavelet Feature Arrangement and Convolutional Neural Networks Deep Learning

Chun Liu, Jianfeng Che, Bo Wang, 2021, IEEE Transactions on Industry Applications.

EALSTM-QR: Interval wind-power prediction model based on numerical weather prediction and deep learning

Xiaosheng Peng, Shanxu Duan, Tao Cai, 2021 .

A Novel Efficient DLUBE Model Constructed by Error Interval Coefficients for Clustered Wind Power Prediction

Xiaosheng Peng, Shanxu Duan, Tao Cai, 2021, IEEE Access.