10 citations · 10 across the 4 of their papers we have counts for
4 papers
Physics-Informed Extreme Learning Machine (PIELM): Opportunities and Challenges
He Yang, Fei Ren, Francesco Calabro +3
We are delighted to see the recent development of physics-informed extreme learning machine (PIELM) for its higher computational efficiency and accuracy compared to other physics-i…
General Fourier Feature Physics-Informed Extreme Learning Machine (GFF-PIELM) for High-Frequency PDEs
Fei Ren, Sifan Wang, Pei-Zhi Zhuang +2
Conventional physics-informed extreme learning machine (PIELM) often faces challenges in solving partial differential equations (PDEs) involving high-frequency and variable-frequen…
Physics-informed extreme learning machine for Terzaghi consolidation problems and interpretation of coefficient of consolidation based on CPTu data
He Yang, Pin-Qiang Mo, Fei Ren +3
This paper conducts a preliminary study to investigate the feasibility of a physics-informed extreme learning machine (PIELM) for solving the Terzaghi consolidation equation and in…
Cylindrical cavity expansion analysis under partially drained conditions for normalisation of excess water pressure in CPTU
He Yang, Pei-Zhi Zhuang, Hai-Sui Yu +4
Cone tip resistance and excess water pressure (EWP) measured by piezocone penetration tests (CPTU) may be significantly affected by the partially drained effect in soils with inter…