Alternative Regression Approach for Data-Driven Power Flow Linearization Methods

Author(s):  
Gopal Jain ◽  
Suraj Sidar ◽  
Deep Kiran
2019 ◽  
Vol 10 (3) ◽  
pp. 2569-2580 ◽  
Author(s):  
Yuxiao Liu ◽  
Ning Zhang ◽  
Yi Wang ◽  
Jingwei Yang ◽  
Chongqing Kang

2021 ◽  
Vol 4 (3) ◽  
pp. 1-16
Author(s):  
Giulio Ortali ◽  
◽  
Nicola Demo ◽  
Gianluigi Rozza ◽  

<abstract><p>This work describes the implementation of a data-driven approach for the reduction of the complexity of parametrical partial differential equations (PDEs) employing Proper Orthogonal Decomposition (POD) and Gaussian Process Regression (GPR). This approach is applied initially to a literature case, the simulation of the Stokes problem, and in the following to a real-world industrial problem, within a shape optimization pipeline for a naval engineering problem.</p></abstract>


2020 ◽  
Vol 189 ◽  
pp. 106567
Author(s):  
Ilyes Mezghani ◽  
Sidhant Misra ◽  
Deepjyoti Deka

2020 ◽  
Vol 11 (2) ◽  
pp. 1077-1090 ◽  
Author(s):  
Weigao Sun ◽  
Mohsen Zamani ◽  
Mohammad Reza Hesamzadeh ◽  
Hai-Tao Zhang

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