Deeppipe: Theory-guided neural network method for predicting burst pressure of corroded pipelines

Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data

Anuj Karpatne, Gowtham Atluri, James H. Faghmous et al. · IEEE Transactions on Knowledge and Data Engineering · 2017 · 1.4K citations · Full text

Engineering, Semantic Web, Theory-guided Data Science +19

Deep learning of subsurface flow via theory-guided neural network

Nanzhe Wang, Dongxiao Zhang, Haibin Chang et al. · Journal of Hydrology · 2020 · 299 citations · Full text

Geometric Learning, Engineering, Machine Learning +1

Carbon trading volume and price forecasting in China using multiple machine learning models

Hongfang Lü, Xin Ma, Kun Huang et al. · Journal of Cleaner Production · 2019 · 280 citations

Forecasting Methodology, Carbon Emission Trading, Engineering +11

Deep learning based forecasting of photovoltaic power generation by incorporating domain knowledge

Xing Luo, Dongxiao Zhang, Xu Zhu · Energy · 2021 · 277 citations · Full text

Engineering, Machine Learning, Photovoltaic System +18

Leakage detection techniques for oil and gas pipelines: State-of-the-art

Hongfang Lü, Tom Iseley, Saleh Behbahani et al. · Tunnelling and Underground Space Technology · 2020 · 270 citations

Petroleum Machinery, Leakage Detection Techniques, Engineering +5