范成
Personal information
Highest Degree：Doctoral degree
Professional Title：Associate professor
Administrative Position：建设管理与房地产系主任、中澳BIM与智慧建造联合研究中心副主任
Academic Honor:
2017 Shenzhen Overseas High-Caliber Personnel Peacock Plan Level C
2023 Shenzhen University "Liyuan Outstanding Yung Scholar"
Journal Paper
- [1]Statistical investigations of transfer learning-based methodology for short-term building energy predictions.,Applied Energy,2020-03-01.
- [2]A graph mining-based methodology for discovering and visualizing high-level knowledge for building energy management,Applied Energy,2019-10-01.
- [3]A short-term building cooling load prediction method using deep learning algorithms,APPLIED ENERGY,.
- [4]Discovering gradual patterns in building operations for improving building energy efficiency,APPLIED ENERGY,.
- [5]Analytical investigation of autoencoder-based methods for unsupervised anomaly detection in building energy data,APPLIED ENERGY,.
- [6]Deep learning-based feature engineering methods for improved building energy prediction,APPLIED ENERGY,2019-04-01.
- [7]Assessment of deep recurrent neural network-based strategies for short-term building energy predictions,APPLIED ENERGY,2019-02-01.
- [8]A novel methodology to explain and evaluate data-driven building energy performance models based on interpretable machine learning,APPLIED ENERGY,2019-02-01.
- [9]Unsupervised data analytics in mining big building operational data for energy efficiency enhancement: A review,ENERGY AND BUILDINGS,2019-01-01.
- [10]基于可解读机器学习的建筑冷负荷预测模型评估方法,建筑节能,2019-09-01.