Area of research
Control and Systems Engineering · Biomedical Engineering
Research interest
Research focused on Artificial neural network and Transformer, with related work in Demand response, Probabilistic neural network, Mathematical optimization. Notable publications include 'Robust capacity optimization methods for integrated energy systems considering demand response and thermal comfort', 'BA-PNN-based methods for power transformer fault diagnosis', and 'Multi-objective optimal scheduling for CCHP microgrids considering peak-load reduction by augmented ε -constraint method'.
Comprehensive review of Transformer‐based models in neuroscience, neurology, and psychiatry
Prior knowledge-embedded meta-transfer learning for few-shot fault diagnosis under variable operating conditions
Tensor representation-based transferability analytics and selective transfer learning of prognostic knowledge for remaining useful life prediction across machines
Conventional and advanced exergy-exergoeconomic-exergoenvironmental analyses of an organic Rankine cycle integrated with solar and biomass energy sources
Multi-objective optimization of hydrogen production system based on the combined supercritical cycle and gas turbine plant
Robust capacity optimization methods for integrated energy systems considering demand response and thermal comfort
Multi-objective optimal scheduling for CCHP microgrids considering peak-load reduction by augmented <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"><mml:mrow><mml:mi mathvariant="normal">ε</mml:mi></mml:mrow></mml:math>-constraint method
A Case-based Reasoning Approach for Supporting Facilitation in Online Discussions
A Hybrid machine‐learning method for oil‐immersed power transformer fault diagnosis
BA-PNN-based methods for power transformer fault diagnosis
Fault Diagnosis in Chemical Processes Based on Class-Incremental FDA and PCA
An optimized GRNN‐enabled approach for power transformer fault diagnosis
A Case-Based Reasoning Approach for Facilitating Online Discussions
Machine Learning-Based Sensor Data Modeling Methods for Power Transformer PHM
A Joint Multi-Feature and Scale-Adaptive Correlation Filter Tracker
A Case-based Reasoning Approach for Automated Facilitation in Online Discussion Systems
A practical solution for HVAC prognostics: Failure mode and effects analysis in building maintenance
Collision detection for virtual environment using particle swarm optimization with adaptive cauchy mutation
Particle filtering-based methods for time to failure estimation with a real-world prognostic application
Data mining-based methods for fault isolation with validated FMEA model ranking