Honglin Wen

According to our database, Honglin Wen authored at least 15 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

A Contextual Bandit Approach for Value-Oriented Prediction Interval Forecasting.

Yufan Zhang, Honglin Wen, Qiuwei Wu

IEEE Trans. Smart Grid, 2024

Tackling Missing Values in Probabilistic Wind Power Forecasting: A Generative Approach.

Honglin Wen, Pierre Pinson, Jie Gu, Zhijian Jin

CoRR, 2024

2023

Optimal Adaptive Prediction Intervals for Electricity Load Forecasting in Distribution Systems via Reinforcement Learning.

Yufan Zhang, Honglin Wen, Qiuwei Wu, Qian Ai

IEEE Trans. Smart Grid, July, 2023

Deriving Loss Function for Value-oriented Renewable Energy Forecasting.

Yufan Zhang, Honglin Wen, Yuexin Bian, Yuanyuan Shi

CoRR, 2023

Value-oriented Renewable Energy Forecasting for Coordinated Energy Dispatch Problems at Two Stages.

Yufan Zhang, Mengshuo Jia, Honglin Wen, Yuanyuan Shi

CoRR, 2023

Probabilistic Wind Power Forecasting with Missing Values via Adaptive Quantile Regression.

Honglin Wen

CoRR, 2023

Fast Constraint Screening for Multi-Interval Unit Commitment.

Xuan He, Jiayu Tian, Yufan Zhang, Honglin Wen, Yize Chen

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

Skeleton Sequence and RGB Frame Based Multi-Modality Feature Fusion Network for Action Recognition.

Xiaoguang Zhu, Ye Zhu, Haoyu Wang, Honglin Wen, Yan Yan, Peilin Liu

ACM Trans. Multim. Comput. Commun. Appl., 2022

Enabling Fast Unit Commitment Constraint Screening via Learning Cost Model.

Xuan He, Honglin Wen, Yufan Zhang, Yize Chen

CoRR, 2022

Targeted Demand Response: Formulation, LMP Implications, and Fast Algorithms.

Yufan Zhang, Honglin Wen, Tao Feng, Yize Chen

CoRR, 2022

Continuous and Distribution-free Probabilistic Wind Power Forecasting: A Conditional Normalizing Flow Approach.

Honglin Wen, Pierre Pinson, Jinghuan Ma, Jie Gu, Zhijian Jin

CoRR, 2022

Wind energy forecasting with missing values within a fully conditional specification framework.

Honglin Wen, Pierre Pinson, Jie Gu, Zhijian Jin

CoRR, 2022

2021

Probabilistic Load Forecasting via Neural Basis Expansion Model Based Prediction Intervals.

Honglin Wen, Jie Gu, Jinghuan Ma, Lyuzerui Yuan, Zhijian Jin

IEEE Trans. Smart Grid, 2021

2020

Unearthing Details of Time Series of Load: A Dual-scale Input Structured LSTM Approach.

Lyuzerui Yuan, Jinghuan Ma, Jie Gu, Honglin Wen, Zhijian Jin

Proceedings of the e-Energy '20: The Eleventh ACM International Conference on Future Energy Systems, 2020

2019

Probabilistic Wind Power Forecasting via Bayesian Deep Learning Based Prediction Intervals.

Honglin Wen, Jie Gu, Jinghuan Ma, Zhijian Jin

Proceedings of the 17th IEEE International Conference on Industrial Informatics, 2019