42 citations · 92 across the 9 of their papers we have counts for
5 papers · 1 filter
Integrating Symbolic Neural Networks with Building Physics: A Study and Proposal
Xia Chen, Guoquan Lv, Xinwei Zhuang +3
Symbolic neural networks, such as Kolmogorov-Arnold Networks (KAN), offer a promising approach for integrating prior knowledge with data-driven methods, making them valuable for ad…
Machine Learning in Proton Exchange Membrane Water Electrolysis -- Part I: A Knowledge-Integrated Framework
Xia Chen, Alexander Rex, Janis Woelke +4
In this study, we propose to adopt a novel framework, Knowledge-integrated Machine Learning, for advancing Proton Exchange Membrane Water Electrolysis (PEMWE) development. Given th…
Utilizing Domain Knowledge: Robust Machine Learning for Building Energy Prediction with Small, Inconsistent Datasets
Xia Chen, Manav Mahan Singh, Philipp Geyer
The demand for a huge amount of data for machine learning (ML) applications is currently a bottleneck in an empirically dominated field. We propose a method to combine prior knowle…
A Dynamic Feedforward Control Strategy for Energy-efficient Building System Operation
Xia Chen, Xiaoye Cai, Alexander Kümpel +2
The development of current building energy system operation has benefited from: 1. Informational support from the optimal design through simulation or first-principles models; 2. S…
Explainable AI for Engineering Design: A Unified Approach of Systems Engineering and Component- Based Deep Learning Demonstrated by Energy- Efficient Building Design
Philipp Geyer, Manav Mahan Singh, Xia Chen
Data-driven models created by machine learning, gain in importance in all fields of design and engineering. They, have high potential to assist decision-makers in creating novel, a…