Machine learning-based thermal response time ahead energy demand prediction for building heating systemsYabin Guo, Yao Huang, Jiangyan Liu et al.|Applied Energy|2018Cited by 205
Deep learning-based fault diagnosis of variable refrigerant flow air-conditioning system for building energy savingYabin Guo, Tanveer Ahmad, Huanxin Chen et al.|Applied Energy|2018Cited by 169
Data partitioning and association mining for identifying VRF energy consumption patterns under various part loads and refrigerant charge conditionsGuannan Li, Miao Sun, Jiangyan Liu et al.|Applied Energy|2016Cited by 99
An improved decision tree-based fault diagnosis method for practical variable refrigerant flow system using virtual sensor-based fault indicatorsGuannan Li, Jiong Li, Jiangyan Liu et al.|Applied Thermal Engineering|2017Cited by 91
A robust online refrigerant charge fault diagnosis strategy for VRF systems based on virtual sensor technique and PCA-EWMA methodJiangyan Liu, Jiong Li, Guannan Li et al.|Applied Thermal Engineering|2017Cited by 48